Head, Data & Artificial Intelligence, Business Transformation (Corporate & Investment Banking, Technology)

ATS Client; Johannesburg; On-site; ZAR 900,000 - 1,500,000; Full time

Job summary

ATS Client in Johannesburg seeks a Senior Data Scientist to oversee data mining, statistical analysis, and modelling across large structured and unstructured datasets to uncover insights and drive business decisions. You will lead methodological work and collaborate with data and technology teams.

Experience with Hadoop ecosystem (HDFS, Spark, Kafka) and tools like SAS/SPSS is required; you will supervise junior staff and productionalise analytics solutions to improve outcomes.

Qualifications

• Postgraduate degree in IT/Information Studies.
• 8–10 years with unstructured data and data mining.
• 8–10 years in software/IA field; BI and governance experience.
• Knowledge of banks data processes and regulatory considerations.
• Experience with SAS/SPSS and data visualization tools.

Responsibilities

• Oversee data mining and statistical analysis on large datasets.
• Develop predictive models and machine learning solutions.
• Lead validation, training, and junior staff guidance on models.
• Coordinate productionalising automation software and IA plans.
• Guide design of statistical methods to answer business questions.
• Drive analytics to improve business outcomes with data-driven insights.

Skills

Data mining

Statistical analysis

Machine learning

Data visualization

Python

R

Education

Postgraduate Degree: Information Technology /Information Studies

Tools

Hadoop

Spark

Kafka

HDFS

SAS

SPSS

Job description

Job Description

Oversee data mining techniques and conduct statistical analysis to large, structured and unstructured data sets to understand and analyse phenomena. Model complex business problems, discovering insights and opportunities through statistical, algorithmic, machine learning and visualisation techniques, working closely with clients, data and technology teams to turn data into critical information used to make sound business decisions. Oversee predictive modelling.

• Acts as a subject matter expert from a data science perspective and provides input into all decisions relating to data science and the use thereof. Educate the organisation on data science perspectives on new approaches, such as testing hypotheses and statistical validation of results. Validates and certifies the work of other data scientists and trains team members in statistical models and guides junior colleagues or less experienced staff on projects and drives leading practice.
• Builds machine learning models from and utilises distributed data processing and analysis methodologies. Competent in Machine Learning programming in R or Python, with supplementary still in Matlab, Java, etc. Familiar with the Hadoop distributed computational platform, including broader ecosystem of tools such as HDFS / Spark / Kafka.
• Codes, tests and maintains scientific models and algorithms; identifies trends, patterns, and discrepancies in data; and determines additional data needed to support insight. Processes, cleanses, and verifies the integrity of data used for analysis.
• Develops, implements, monitors and maintains a comprehensive operational IA plan, rules, methodologies and coding initiatives in order to drive IA for remediation efforts. Develops and co-ordinates a comprehensive strategy for productionalising automation software so that it is accurate and well maintained.
• Guides and validates the design of various complex mathematical, statistical, and simulation techniques to answer critical business questions and create predictive solutions which drive improvement in business outcomes. Drives analytics and insights within required business unit by developing advanced statistical models and computational algorithms based on business initiatives.

Qualifications

• Post Graduate Degree: Information Technology /Information Studies (required)

Experience Required

Data Monetisation

• 8-10 years: Experience in working with unstructured data (e.g. Streams, images). Understanding of data flows, data architecture, ETL and processing of structured and unstructured data. Using data mining to discover new patterns from large datasets. Implement standard and proprietary algorithms for handling and processing data. Experience with common data science toolkits, such as SAS, R, SPSS, etc. Experience with data visualisation tools, such as Power BI, Tableau, etc.
• 8-10 years: Proven development experience in software / software engineering. Up to date with developments in IA field. Experience in technical business intelligence; in depth understanding of the banks data processes, systems and products. Knowledge of IT infrastructure and data principles forming the basis for data quality management. Project management experience. Exposure to data governance and regulatory matters. Experience in building models (credit scoring, propensity models, churn, etc).

Behavioural Competencies

• Adopting Practical Approaches
• Articulating Information
• Challenging Ideas
• Exploring Possibilities
• Interpreting Data

Technical Competencies

• Data Analysis
• Database Administration
• Data Integrity
• Knowledge Classification
• Research & Information Gathering