Careers

CAREERS

Are you interested to join the Cortex Logic team?

Cortex Logic is on a mission to help shape a better future in the Smart Technology Era by providing an AI Engine for Business that solves strategic and operationally relevant problems through operationalizing Data Science, Internet of Things and Big Data & Analytics and delivering state-of-the-art AI-based applications, solutions and products. In order to this we are building a world-class team of artificial intelligence and machine learning experts, data scientists, data and solution architects, data engineers, business intelligence engineers, business analysts, software developers, domain experts, and out-of-the-box thinkers.  We welcome partners and like-minded people that share our passion and vision. Although we are currently based in South Africa and India, we operate in a virtual way with people around the globe. Anyone interested to join the Cortex Logic team, can fill in the form below.

Current Openings

Senior Data Scientists

Key responsibilities

  • Maximise usable information by productising intelligence in a collaborative, automated, and scalable way
  • Development of predictive models (e.g. credit scoring; disbursement; collection rate; retention; repeat rate; customer acquisition; fraud detection; segmentation; social network analysis; etc.)
  • Development of data processes to mine value from a variety of data sources that include high-volume, transaction-level data
  • Provision of analytical and visualization tools and algorithms to various other business teams
  • Contribution to the development of machine learning
  • Design and development of algorithms which will constitute components of an intelligent decision platform
  • Operationalization of Big Data & Analytics
  • Collaboration with system developers, data engineers, and data architect to implement all of the above.

Skills, competencies, and experience

The applicant must have the following skills, competencies and experience (or a significant subset thereof):

  • A Masters or Ph.D degree in Computer Science, Mathematics, Physics, Statistics, or similar
  • MOOC courses and/or training in state-of-the-art Analytics, Data Science, Machine Learning, Machine Intelligence, Artificial Intelligence, Data Analysis, Programming, etc.
  • Track record of delivering on Data Science related projects
  • Strong background in data preparation, analysis, and building of machine learning and statistical models to generate insights and solving real-world problems
  • A mixture of multidisciplinary skills ranging from an intersection of computer science, mathematics, statistics, communication and business.
  • Deep knowledge and experience with machine learning and artificial intelligence.
  • Strong mathematical aptitude and problem solving ability
  • Ability to work independently, but also a strong team ethic
  • Proven ability to complete projects
  • Excellent oral and written communication skills
  • High levels of energy and drive
  • Math & Statistics: machine learning; statistical modeling, experient design, supervised learning (deep learning, decision trees, random forests, SVM, logistic regression ,etc.); unsupervised learning (clustering, PCA/PLS, k-means, dimension reduction); Reinforcement learning; Optimization (gradient descent and variants); Bayesian inference
  • Programming & Database: computer science fundamentals, Scripting language, e.g. Python; Stats languages and/or packages, e.g., R, SAS, SPSS; Databases: SQL and NoSQL; Relational Algebra, Parallel databases and parallel query processing; Map reduce concepts; Hadoop, Spark, Hive/Pig, Redshift, S3; Custom reducers; Experience with xaaS like AWS, Azure, etc.; Open source Machine Learning stacks and libraries such a Tensorflow, MXNet, CNTK, Caffe, Theano, Torch, and PyTorch.
  • Domain knowledge & soft skills: Passionate about the business; Curious about data; Influence without authority; Hacker mindset; Problem solver; Strategic, proactive, creative, innovative and collaborative
  • Communication and Visualization: Ability to engage with senior management; story telling skills; Translate data-driven insights into decisions an actions; Visual art design; Python and R visualization packages; Knowledge of anay visualization tools, e.g., Flare, D3.js, Tableau.
Data Scientists

Key responsibilities

  • Maximise usable information by productising intelligence in a collaborative, automated, and scalable way
  • Development of predictive models (e.g. credit scoring; disbursement; collection rate; retention; repeat rate; customer acquisition; fraud detection; segmentation; social network analysis; etc.)
  • Development of data processes to mine value from a variety of data sources that include high-volume, transaction-level data
  • Provision of analytical and visualization tools and algorithms to various other business teams
  • Contribution to the development of machine learning
  • Design and development of algorithms which will constitute components of an intelligent decision platform
  • Operationalization of Big Data & Analytics
  • Collaboration with system developers, data engineers, and data architect to implement all of the above.

Skills, competencies, and experience

The applicant must have the following skills, competencies and experience (or a significant subset thereof):

  • A post graduate, Masters of Ph.D degree in Computer Science, Mathematics, Physics, Statistics, or similar
  • MOOC courses and/or training in state-of-the-art Analytics, Data Science, Machine Learning, Machine Intelligence, Artificial Intelligence, Data Analysis, Programming, etc.
  • Track record of delivering on Data Science related projects
  • Strong background in data preparation, analysis, and building of machine learning and statistical models to generate insights and solving real-world problems
  • A mixture of multidisciplinary skills ranging from an intersection of computer science, mathematics, statistics, communication and business.
  • Deep knowledge and experience with machine learning and artificial intelligence.
  • Strong mathematical aptitude and problem solving ability
  • Ability to work independently, but also a strong team ethic
  • Proven ability to complete projects
  • Excellent oral and written communication skills
  • High levels of energy and drive
  • Math & Statistics: machine learning; statistical modeling, experient design, supervised learning (deep learning, decision trees, random forests, SVM, logistic regression ,etc.); unsupervised learning (clustering, PCA/PLS, k-means, dimension reduction); Reinforcement learning; Optimization (gradient descent and variants); Bayesian inference
  • Programming & Database: computer science fundamentals, Scripting language, e.g. Python; Stats languages and/or packages, e.g., R, SAS, SPSS; Databases: SQL and NoSQL; Relational Algebra, Parallel databases and parallel query processing; Map reduce concepts; Hadoop, Spark, Hive/Pig, Redshift, S3; Custom reducers; Experience with xaaS like AWS, Azure, etc.; Open source Machine Learning stacks and libraries such a Tensorflow, MXNet, CNTK, Caffe, Theano, Torch, and PyTorch.
  • Domain knowledge & soft skills: Passionate about the business; Curious about data; Influence without authority; Hacker mindset; Problem solver; Strategic, proactive, creative, innovative and collaborative
  • Communication and Visualization: Ability to engage with senior management; story telling skills; Translate data-driven insights into decisions an actions; Visual art design; Python and R visualization packages; Knowledge of anay visualization tools, e.g., Flare, D3.js, Tableau.
Artificial Intelligence / Machine Learning Experts

Key responsibilities

  • Maximise usable information by productising intelligence in a collaborative, automated, and scalable way
  • Advancing the state-of-the-art in Artificial Intelligence / Machine Learning via R&D
  • Development of predictive models (e.g. credit scoring; disbursement; collection rate; retention; repeat rate; customer acquisition; fraud detection; segmentation; social network analysis; etc.)
  • Development of data processes to mine value from a variety of data sources that include high-volume, transaction-level data
  • Provision of analytical and visualization tools and algorithms to various other business teams
  • Contribution to the development of machine learning
  • Design and development of algorithms which will constitute components of an intelligent decision platform
  • Operationalization of Big Data & Analytics
  • Collaboration with system developers, data engineers, and data architect to implement all of the above.

Skills, competencies, and experience

The applicant must have the following skills, competencies and experience (or a significant subset thereof):

  • A post graduate, Masters of Ph.D degree in Computer Science, Mathematics, Physics, Statistics, or similar
  • MOOC courses and/or training in state-of-the-art Analytics, Data Science, Machine Learning, Machine Intelligence, Artificial Intelligence, Data Analysis, Programming, etc.
  • Track record of delivering on Data Science related projects
  • Strong background in data preparation, analysis, and building of machine learning and statistical models to generate insights and solving real-world problems
  • A mixture of multidisciplinary skills ranging from an intersection of computer science, mathematics, statistics, communication and business.
  • Deep knowledge and experience with machine learning and artificial intelligence.
  • Strong mathematical aptitude and problem solving ability
  • Ability to work independently, but also a strong team ethic
  • Proven ability to complete projects
  • Excellent oral and written communication skills
  • High levels of energy and drive
  • Math & Statistics: machine learning; statistical modeling, experient design, supervised learning (deep learning, decision trees, random forests, SVM, logistic regression ,etc.); unsupervised learning (clustering, PCA/PLS, k-means, dimension reduction); Reinforcement learning; Optimization (gradient descent and variants); Bayesian inference
  • Programming & Database: computer science fundamentals, Scripting language, e.g. Python; Stats languages and/or packages, e.g., R, SAS, SPSS; Databases: SQL and NoSQL; Relational Algebra, Parallel databases and parallel query processing; Map reduce concepts; Hadoop, Spark, Hive/Pig, Redshift, S3; Custom reducers; Experience with xaaS like AWS, Azure, etc.; Open source Machine Learning stacks and libraries such a Tensorflow, MXNet, CNTK, Caffe, Theano, Torch, and PyTorch.
  • Domain knowledge & soft skills: Passionate about the business; Curious about data; Influence without authority; Hacker mindset; Problem solver; Strategic, proactive, creative, innovative and collaborative
  • Communication and Visualization: Ability to engage with senior management; story telling skills; Translate data-driven insights into decisions an actions; Visual art design; Python and R visualization packages; Knowledge of anay visualization tools, e.g., Flare, D3.js, Tableau.
Data Science Developers

Key responsibilities

  • Build big data transformation and querying platforms
  • Design, implement, test, document and maintain systems that:
    • Transforms Big Data, i.e. aggregate, feature extraction, etc.
    • Query on Big Data
    • Large scale automation of deployment, execution and monitoring of Predictive Analytics, Machine Learning Models and other Data Products
  • Maximise usable information by productising intelligence in a collaborative, automated, and scalable way
  • Development support for:
    • Development of predictive models (e.g. credit scoring; disbursement; collection rate; retention; repeat rate; customer acquisition; fraud detection; segmentation; social network analysis; etc.)
    • Development of data processes to mine value from a variety of data sources that include high-volume, transaction-level data
    • Provision of analytical and visualization tools and algorithms to various other business teams
    • Contribution to the development of machine learning
    • Design and development of algorithms which will constitute components of an intelligent decision platform
  • Operationalization of Big Data & Analytics
  • Collaboration with system developers, data engineers, and data architect to implement all of the above.

Skills, competencies, and experience

The applicant must have the following skills, competencies and experience (or a significant subset thereof):

  • A post graduate, Masters of Ph.D degree in Computer Science, Electronic Engineering, Mathematics, Physics, Statistics, or similar
  • MOOC courses and/or training in state-of-the-art Analytics, Data Science, Machine Learning, Machine Intelligence, Artificial Intelligence, Data Analysis, Programming, etc.
  • Strong background in software development using a modern object oriented software development language
  • Understand the SDLC (Software Development Lifecycle)
  • Experience documenting and communicating designs
  • Experience using databases and query languages
  • Experience using a DVCS (Distributed Version Control System)
  • Experience working in an agile environment, using agile development practices, e.g. Scrum or Kanban
  • Experience working within a team context
  • Understanding web application development fundamentals and practices
  • Understanding of and experience with using functional programming language concepts
  • Experience developing scalable, reliable and fault tolerant systems
  • Experience with AWS (Amazon Web Services)
  • Experience with DevOps
  • Passion for software development and technology
  • Ability to quickly master new concepts and development paradigms
  • Ability to work independently, but also in a team
  • Problem solving ability
  • Excellent oral and written communication skills
  • Curiosity and daring to challenge the status quo
  • Basic knowledge of machine learning
  • Programming: Python, Java, Scala, HTML and JavaScript
  • Database: Concepts and SQL
  • Ability to develop in a Unix based environment (Mac/Linux)
  • Software Design Patterns: Architectural, Creational, Structural Behavioural and Concurrency Patterns
  • Understanding of the Amazon Web Services (AWS) or other similar Cloud Platforms (Azure, etc.) landscape and concepts
  • Software Design Patterns: Enterprise Integration Patterns
  • Git
  • Spark
  • Hadoop

Desirable

  • Strong background in data preparation, analysis, and building of machine learning and statistical models to generate insights and solving real-world problems
  • A mixture of multidisciplinary skills ranging from an intersection of computer science, mathematics, statistics, communication and business.
  • Deep knowledge and experience with machine learning and artificial intelligence.
  • Track record of delivering on Data Science related projects
  • Strong mathematical aptitude and problem solving ability
  • Math & Statistics: machine learning; statistical modeling, experient design, supervised learning (deep learning, decision trees, random forests, SVM, logistic regression ,etc.); unsupervised learning (clustering, PCA/PLS, k-means, dimension reduction); Reinforcement learning; Optimization (gradient descent and variants); Bayesian inference
  • Programming & Database: computer science fundamentals, Scripting language, e.g. Python; Stats languages and/or packages, e.g., R, SAS, SPSS; Databases: SQL and NoSQL; Relational Algebra, Parallel databases and parallel query processing; Map reduce concepts; Hadoop, Spark, Hive/Pig, Redshift, S3; Custom reducers; Experience with xaaS like AWS, Azure, etc.; Open source Machine Learning stacks and libraries such a Tensorflow, MXNet, CNTK, Caffe, Theano, Torch, and PyTorch.
  • Domain knowledge & soft skills: Passionate about the business; Curious about data; Influence without authority; Hacker mindset; Problem solver; Strategic, proactive, creative, innovative and collaborative
  • Communication and Visualization: Ability to engage with senior management; story telling skills; Translate data-driven insights into decisions an actions; Visual art design; Python and R visualization packages; Knowledge of anay visualization tools, e.g., Flare, D3.js, Tableau.
Data Architects

Key responsibilities

  • Define vision, strategy and principles for data management
  • Define standards for naming, describing, governing, managing, modeling, cleansing, enriching, transforming, moving, storing, searching & delivering all data within enterprise
  • Serve as the liaison between data consumer representatives and data solution development, integration and governance teams
  • Inform and interpret data project sponsors
  • Must understand how data is, or will be, used and implication on people, processes, products and technology
  • Determines database structural requirements by analyzing client operations, applications, and programming; reviewing objectives with clients; evaluating current systems;
  • Develops database solutions by designing proposed system; defining database physical structure and functional capabilities, security, back-up, and recovery specifications.
  • Installs database systems by developing flowcharts; applying optimum access techniques; coordinating installation actions; documents actions.
  • Maintains database performance by identifying and resolving production and application development problems; calculating optimum values for parameters; evaluating, integrating, & installing new releases; completing maintenance; answering user questions.
  • Prepares users by conducting training.
  • Provides database support by coding utilities, responding to user questions, and resolving problems.
  • Updates job knowledge by participating in educational opportunities; reading professional publications; maintaining personal networks; participating in professional organizations.
  • Accomplishes information systems and organization mission by completing related results as needed.

 

High-level Data Architecture Tasks

  • Define and Implement:
    • Enterprise Data Vision and Strategy
    • Enterprise Data Scoped Roadmap
    • Enterprise Data Standard
    • Enterprise Data Model
    • Enterprise Data Governance Functions and Frameworks
    • Enterprise Data Technology Use Map
    • Enterprise Information Analysis Maps
    • Reference, Master, Meta Data and Document Practices
  • Set Goals and Measure:
    • Data Project Progress
    • Data Quality Improvements
    • Data Compliance Level
  • Sponsor, Lead and Participate:
    • Enterprise Data Initiatives
    • Industry Data Initiatives

 

Data Domains to Master

  • Data Strategy and Data Governance
    • Data Architecture Roadmap Evangelism
    • Data Store and Tool Vendor Evaluations
    • Data Policies, Processes and Standards
    • Data Architecture Reviews and Issue Resolution
  • Data Modeling
    • Conceptual Data Modeling
    • Canonical Data Modeling
    • Logical Data Modeling
    • Data Object Modeling
    • Relational Modeling
    • Document Modeling
    • Analytics Modeling
  • Data Store Definition
    • Topology and Virtualization Modeling
    • Data Federation Modeling
    • Performance, Scaling, Caching
  • Data Content Management
    • Reference Data Management
    • Master Data Management
    • Meta-Data Management
    • Data Life Cycle Management
    • Data Quality Management
    • Corporate and Regulatory Compliance
  • Data Asset Discovery and Access
    • Data Store Inventory Discovery
    • Data Security and API Control
    • Data Languages
  • Data Analysis
    • Business Intelligence Reporting
    • Predictive/Reactive Decision Support
    • Business Rule Management
    • Data Warehouses, Data Marts
    • Data Migration, ETL, Archive

 

Skills, competencies, and experience

The applicant must have the following skills, competencies and experience (or a significant subset thereof):

  • Database Design, Data Maintenance, Database Security, Database Management, Requirements Analysis, Teamwork, Technical Zeal, Project Management, Presenting Technical Information, Training , Operating System
  • Have a Bachelor’s, Honours or preferably a Master’s degree in computer science or software engineering or similar fields
  • Proficient in designing efficient and robust ETL workflows
  • To be able to work with cloud computing environments
  • Be able to work in teams and collaborate with others to clarify requirements
  • Assist in documenting requirements as well as resolve conflicts or ambiguities
  • Strong team player. The ability to work and integrate with multiple teams.
  • To enjoy being challenged and to solve complex problems on a daily basis
  • Development experience in Python / Java
  • Scripting experience.
  • DBA experience in MySQL / MS SQL / Redshift
  • Corporate Strategy Analysis
  • Strategy, Project and Product Risk Assessment
  • Enterprise and Functional Modeling
  • Product Requirements Interpretation
  • Product Reviews and Governance
  • Collaborative Project Team Management
  • Software Development Methods
  • Software Release Life Cycle Management
  • Foster relationships with key stakeholders
  • IT Management
  • Relevant Industry Domain Knowledge
  • Positive Passionate Influential Inspirational Leadership and Mentor Attitude
  • Excellent Written, Verbal, Virtual and Live Communication Skills
Data Engineers

Key responsibilities

  • Deliver a high quality, responsive and efficient data acquisition service supporting company and customer objectives through delivery of data to support analysis.
  • Ensure integrity, consistency, and accuracy of data received and making sure that all internal teams have a clear understanding of the raw data.
  • Collaborate with internal customers to continuously refine data acquisition requirements.
  • In close collaboration with other teams, build and manage a relationship with external partners with respect to data acquisition and ensure high quality and timeous / continues delivery of data
  • As a member of the Data Engineering team ensures that data is extracted, transformed and loaded into our cloud-based data warehouse with automated processes developed, tested, integrated and meeting the company requirements in this regard (e.g., appropriate validation and data quality assurance)
  • Supports maximization of usable information by productising intelligence in a collaborative, automated, and scalable way
  • Build, maintain and support data pipeline.
  • Communicate with external partners to insure the timeous / continues delivery of data
  • Developed and automate processes in Amazon Web Services / Cloud platforms
  • Support the data pipeline / databases
  • Develop applications to facilitate processes around data.
  • Emplement ETL processes
  • Monitoring performance and advise of any necessary infrastructure change
  • Securing data in accordance with company policy.
  • Creating and maintaining applicable documentation for information and knowledge sharing.
  • Manage data enrichment with respect to collecting other external contextual data that can be overlayed with Cortex Logic and/or customer’s current data sets.

Skills, competencies, and experience

The applicant must have the following skills, competencies and experience (or a significant subset thereof):

  • Have a Bachelor’s or post graduate degree in computer science or software engineering
  • Excellent oral and written communication skills
  • Proficient in designing efficient and robust ETL workflows
  • To be able to work with cloud computing environments
  • Be able to work in teams and collaborate with others to clarify requirements
  • Assist in documenting requirements as well as resolve conflicts or ambiguities
  • Strong team player. The ability to work and integrate with multiple teams.
  • To enjoy being challenged and to solve complex problems on a daily basis
  • Development experience in Python / Java / Shell scripting / Scala
  • DBA experience in MySQL / MS SQL / Redshift / other relational DBs
  • NoSQL DBs
  • SFTP / Linux experience
  • Cloud platforms
Senior Business Intelligence Analysts

Key responsibilities

  • Business Intelligence analyst responsibilities as it pertains to:
    • Data preparation (sourcing, acquisition, integration)
    • Data warehousing (we often recommend that the first two functional areas are managed separately by “data preparation” team(s))
    • Reporting, analytics, data exploration
    • Information delivery (portals, mobile)
  • Delivery of information and analytics platforms and solutions to the business’s key stakeholders, including, internal staff, partners and clients.
  • Helping customers transform into a business that truly differentiates and competes on analytics.
  • BI competency center or center of excellence
  • Develops dynamic ETL frameworksthat can handle data loading, quality and integrity checks and provide accurate reporting. 
  • Partners proactively with internal and external teams to drive impact, re-enforces the core effort and commercial application, democratizes and scales BI and its use effectively throughout the organization and partner network, and forges strong paths for operationalization to deliver the real monetary impact.
  • Help to ensure an optimized process maturity, and uses a state-of-the-art BI environment and fit-for-purpose tools for fast and effective delivery of business insights
  • Create meaningful, easy to understand dashboards that highlight product development and enterprise wide delivery.
  • Create platform whereby any data source can be plugged in and integrated to existing data and enable quick and easy reporting of all data.

 

Skills, competencies, and experience

The applicant must have the following skills, competencies and experience (or a significant subset thereof):

  • A Bachelors, Honours or Masters degree in computer science, mathematics, operations, management, or a related field is required.
  • A minimum of 5-10 years of progressively responsible experience in a directly related area, during which both professional and management capabilities have been clearly demonstrated.
  • MOOC courses and/or training in Business Intelligence, Analytics, Data Science, Machine Learning, Data Analysis, Programming, etc.
  • Track record of delivering on Business Intellience related projects
  • Extensive expertise in BI and related technical platforms.
  • Extensive expertise in data modeling, both logical and physical.
  • Extensive experience in multidimensional data modeling, such as star schemas, snowflakes, denormalized models, handling “slow-changing” dimensions/attributes.
  • Experience in and understanding of a wide variety of analytical processes (governance, measurement, etc.).
  • Proficient in designing efficient and robust ETL workflows
  • To be able to work with cloud computing environments
  • Be able to work in teams and collaborate with others to clarify requirements
  • Assist in documenting requirements as well as resolve conflicts or ambiguities
  • Strong team player. The ability to work and integrate with multiple teams.
  • To enjoy being challenged and to solve complex problems on a daily basis
  • Scripting experience.
  • DBA experience in MySQL / MS SQL / Redshift
  • Experience with agile software development.
  • A solid understanding of key BI trends.
  • Excellent written and verbal communication skills.
  • Excellent presentation skills.
  • Experience managing large complex BI projects and teams.
  • Proven ability to complete projects and achieve results in an ambiguous work environment.
  • Proven strong leadership skills within the project team and in the business community.
  • Proven ability to establish and articulate a vision, set goals, develop and execute strategies, and track and measure results.
  • Proven ability to build and motivate a team to achieve well communicated expectations.
  • Proven strong negotiating and consensus building abilities.
  • Proven skills to work effectively across internal functional areas in ambiguous situations
Business Intelligence Analysts

Key responsibilities

  • Business Intelligence analyst responsibilities as it pertains to:
    • Data preparation (sourcing, acquisition, integration)
    • Data warehousing (we often recommend that the first two functional areas are managed separately by “data preparation” team(s))
    • Reporting, analytics, data exploration
    • Information delivery (portals, mobile)
  • Delivery of information and analytics platforms and solutions to the business’s key stakeholders, including, internal staff, partners and clients.
  • Helping customers transform into a business that truly differentiates and competes on analytics.
  • BI competency center or center of excellence
  • Develops dynamic ETL frameworksthat can handle data loading, quality and integrity checks and provide accurate reporting. 
  • Partners proactively with internal and external teams to drive impact, re-enforces the core effort and commercial application, democratizes and scales BI and its use effectively throughout the organization and partner network, and forges strong paths for operationalization to deliver the real monetary impact.
  • Help to ensure an optimized process maturity, and uses a state-of-the-art BI environment and fit-for-purpose tools for fast and effective delivery of business insights
  • Create meaningful, easy to understand dashboards that highlight product development and enterprise wide delivery.
  • Create platform whereby any data source can be plugged in and integrated to existing data and enable quick and easy reporting of all data.

 

Skills, competencies, and experience

The applicant must have the following skills, competencies and experience (or a significant subset thereof):

  • A Bachelors, Honours or Masters degree in computer science, mathematics, operations, management, or a related field is required.
  • A minimum of 3-5 years of progressively responsible experience in a directly related area, during which both professional and management capabilities have been clearly demonstrated.
  • MOOC courses and/or training in Business Intelligence, Analytics, Data Science, Machine Learning, Data Analysis, Programming, etc.
  • Track record of delivering on BI related projects
  • Expertise in BI and related technical platforms.
  • Expertise in data modeling, both logical and physical.
  • Experience in multidimensional data modeling, such as star schemas, snowflakes, denormalized models, handling “slow-changing” dimensions/attributes.
  • Experience in and understanding of a wide variety of analytical processes (governance, measurement, etc.).
  • Proficient in designing efficient and robust ETL workflows
  • To be able to work with cloud computing environments
  • Be able to work in teams and collaborate with others to clarify requirements
  • Assist in documenting requirements as well as resolve conflicts or ambiguities
  • Strong team player. The ability to work and integrate with multiple teams.
  • To enjoy being challenged and to solve complex problems on a daily basis
  • Scripting experience.
  • DBA experience in MySQL / MS SQL / Redshift
  • Experience with agile software development.
  • A solid understanding of key BI trends.
  • Excellent written and verbal communication skills.
  • Excellent presentation skills.
  • Experience managing large complex BI projects and teams.
  • Proven ability to complete projects and achieve results in an ambiguous work environment.
  • Proven strong leadership skills within the project team and in the business community.
  • Proven ability to establish and articulate a vision, set goals, develop and execute strategies, and track and measure results.
  • Proven ability to build and motivate a team to achieve well communicated expectations.
  • Proven strong negotiating and consensus building abilities.
  • Proven skills to work effectively across internal functional areas in ambiguous situations
Business Intelligence Developers

Key responsibilities

  • Develops dynamic ETL frameworksthat can handle data loading, quality and integrity checks and provide accurate reporting. 
  • Supports Business Intelligence development responsibilities as it pertains to:
    • Data preparation (sourcing, acquisition, integration)
    • Data warehousing (we often recommend that the first two functional areas are managed separately by “data preparation” team(s))
    • Reporting, analytics, data exploration
    • Information delivery (portals, mobile)
  • Delivery of information and analytics platforms and solutions to the business’s key stakeholders, including, internal staff, partners and clients.
  • Helping customers transform into a business that truly differentiates and competes on analytics.
  • BI competency center or center of excellence
  • Partners proactively with internal and external teams to drive impact, re-enforces the core effort and commercial application, democratizes and scales BI and its use effectively throughout the organization and partner network, and forges strong paths for operationalization to deliver the real monetary impact.
  • Help to ensure an optimized process maturity, and uses a state-of-the-art BI environment and fit-for-purpose tools for fast and effective delivery of business insights
  • Create meaningful, easy to understand dashboards that highlight product development and enterprise wide delivery.
  • Create platform whereby any data source can be plugged in and integrated to existing data and enable quick and easy reporting of all data.

 

Skills, competencies, and experience

The applicant must have the following skills, competencies and experience (or a significant subset thereof):

  • A Bachelors, Honours or Masters degree in computer science, mathematics, operations, management, or a related field is required.
  • A minimum of 3-5 years of progressively responsible experience in a directly related area, during which both professional and management capabilities have been clearly demonstrated.
  • MOOC courses and/or training in Business Intelligence, Analytics, Data Science, Machine Learning, Data Analysis, Programming, etc.
  • Track record of delivering on BI related projects
  • Expertise in BI and related technical platforms.
  • Expertise in data modeling, both logical and physical.
  • Experience in multidimensional data modeling, such as star schemas, snowflakes, denormalized models, handling “slow-changing” dimensions/attributes.
  • Experience in and understanding of a wide variety of analytical processes (governance, measurement, etc.).
  • Proficient in designing efficient and robust ETL workflows
  • To be able to work with cloud computing environments
  • Be able to work in teams and collaborate with others to clarify requirements
  • Assist in documenting requirements as well as resolve conflicts or ambiguities
  • Strong team player. The ability to work and integrate with multiple teams.
  • To enjoy being challenged and to solve complex problems on a daily basis
  • Scripting experience.
  • DBA experience in MySQL / MS SQL / Redshift
  • Experience with agile software development.
  • A solid understanding of key BI trends.
  • Excellent written and verbal communication skills.
  • Excellent presentation skills.
  • Experience managing large complex BI projects and teams.
  • Proven ability to complete projects and achieve results in an ambiguous work environment.
  • Proven strong leadership skills within the project team and in the business community.
  • Proven ability to establish and articulate a vision, set goals, develop and execute strategies, and track and measure results.
  • Proven ability to build and motivate a team to achieve well communicated expectations.
  • Proven strong negotiating and consensus building abilities.
  • Proven skills to work effectively across internal functional areas in ambiguous situations
Software Developers

Key responsibilities

  • Software development as it pertains to developing state-of-the-art smart machine intelligence-based applications and products such as intelligent virtual assistants and advisors, fraud detection, churn prediction, smart risk scoring, smart trading, real-time customer insights, smart recommendations and purchase prediction, and smart payment for finance, healthcare, education, retail, telecoms, industrial and public sector as well as other industries where the automation of tasks can lead to economic benefit, scalability and productivity.
  • Build big data transformation and querying platforms
  • Design, implement, test, document and maintain systems that:
    • Transforms Big Data, i.e. aggregate, feature extraction, etc.
    • Query on Big Data
    • Large scale automation of deployment, execution and monitoring of Predictive Analytics, Machine Learning Models and other Data Products
  • Maximise usable information by productising intelligence in a collaborative, automated, and scalable way
  • Development support for:
    • Development of predictive models (e.g. credit scoring; disbursement; collection rate; retention; repeat rate; customer acquisition; fraud detection; segmentation; social network analysis; etc.)
    • Development of data processes to mine value from a variety of data sources that include high-volume, transaction-level data
    • Provision of analytical and visualization tools and algorithms to various other business teams
    • Contribution to the development of machine learning
    • Design and development of algorithms which will constitute components of an intelligent decision platform
  • Operationalization of Big Data & Analytics
  • Collaboration with system developers, data engineers, and data architect to implement all of the above.

 

Skills, competencies, and experience

The applicant must have the following skills, competencies and experience (or a significant subset thereof):

  • A Bachelors or post graduate degree in Computer Science, Electronic Engineering, Mathematics, Physics, Statistics, or similar
  • Strong background in software development using a modern object oriented software development language
  • Understand the SDLC (Software Development Lifecycle)
  • Experience documenting and communicating designs
  • Experience using databases and query languages
  • Experience using a DVCS (Distributed Version Control System)
  • Experience working in an agile environment, using agile development practices, e.g. Scrum or Kanban
  • Experience working within a team context
  • Understanding web application development fundamentals and practices
  • Understanding of and experience with using functional programming language concepts
  • Experience developing scalable, reliable and fault tolerant systems
  • Experience with AWS (Amazon Web Services)
  • Experience with DevOps
  • Passion for software development and technology
  • Ability to quickly master new concepts and development paradigms
  • Ability to work independently, but also in a team
  • Problem solving ability
  • Excellent oral and written communication skills
  • Curiosity and daring to challenge the status quo
  • Basic knowledge of machine learning
  • Programming: Python, Java, Scala, JavaScript, Swift, HTML
  • Database: Concepts and SQL and NoSQL DBs
  • Ability to develop in a Unix based environment (Mac/Linux)
  • Software Design Patterns: Architectural, Creational, Structural Behavioural and Concurrency Patterns
  • Understanding of the Amazon Web Services (AWS) or other similar Cloud Platforms (Azure, etc.) landscape and concepts
  • Google, IBM, Microsoft andor Amazon Development Tools and Cloud offerings
  • Software Design Patterns: Enterprise Integration Patterns
  • Git, Spark, Hadoop, NodeJS, Electron, Cloud Foundry, etc.

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