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Job Description

Role Summary

We are looking for a Data Scientist – Investment Analytics to join our Technology and Data team. The incumbent must have 5 to 7 years of experience in data science and be passionate about applying machine learning, predictive analytics, and quantitative methods to financial and investment challenges. You will support data-driven investment insights and help enhance portfolio construction, manager evaluation, and performance analytics, working closely with portfolio managers, investment analysts, and risk professionals.

The successful incumbent must be adept at handling large, complex datasets, developing and applying robust analytical processes including data cleansing, data interpretation models, forecasting, pattern identification and trend analysis.

The role requires solid technical skills, practical understanding of financial data, and the ability to collaborate effectively across teams.

Key Responsibilities include:

• Develop and implement machine learning models, predictive analytics, and quantitative strategies to enhance investment decision-making in a multi-manager investment environment.
• Develop models and tools to Support manager due diligence, risk attribution and performance benchmarking, in a multi-management investment environment.
• Collaborate with investment analysts, discretionary fund managers and risk teams to translate business problems into data-driven solutions.
• Build and maintain scalable data pipelines and analytical models to assess investment managers' performance, risk exposures, and factor contributions.
• Contribute to the automation of due diligence processes by developing data-driven frameworks through clean, scalable code and reproducible workflows.
• Provide mentorship to junior analysts or interns where applicable. Stay up to date with emerging technologies and trends in data science, machine learning, and AI relevant to multi-manager investment services.
• Develop interactive dashboards, reports, and APIs to provide real-time insights on manager performance and market conditions.
• Collaborate with IT and data engineering teams to ensure seamless integration of data science models into operational and investment decision processes.

Qualification, Skills and Experience:

Education:

• Bachelor’s or Master’s degree in Data Science, Computer Science, Mathematics, Statistics, Financial Engineering, or a related field.

Experience:

• 5 to 7 years of experience in data science or advanced analytics, preferably in financial services or investment management.
• Experience in building and deploying machine learning and AI models in production environments.
• Exposure to investment concepts such as performance attribution, portfolio construction, risk metrics, or manager due diligence is highly beneficial.

Technical Skills:

• Expertise in Python, SQL, (R optional) and other relevant programming languages for data science and quantitative research.
• Experience with machine learning frameworks (TensorFlow, PyTorch, Scikit-learn, XGBoost, or similar.).
• Exposure to cloud computing platforms (AWS, Azure etc.) and distributed computing (Spark, Dask etc.)
• Experience with big data technologies (Hadoop, Snowflake, Databricks) and data engineering best practices.

Certifications (Preferred):

• Data Science / Artificial Intelligence / Machine Learning Certifications
• CFA (Chartered Financial Analyst) or progress toward CFA designation is advantageous but not required.

Key Competencies:

• Strong analytical and problem-solving skills with the ability to translate complex financial data into actionable insights.
• Ability to communicate technical concepts clearly to both technical and non-technical stakeholders.
• Ability to manage multiple projects simultaneously and deliver results in a fast-paced environment.
• Mentoring capabilities to guide junior data scientists/analysts/engineers.

What We Offer

• Opportunity to apply data science in a purpose-led investment business.
• Exposure to diverse investment strategies and real-world financial applications.
• A collaborative and innovative team culture.
• Flexibility and growth potential in a supportive environment.

Analyse data to draw insights, patterns and conclusions that will enable the business to improve their products, services, processes or to develop new strategies. Must be adept at handling large, complex datasets and developing and applying robust analytical processes including data cleaning, data interpretation models, forecasting, pattern identification and trend analysis. As well as studying product and process-related data, may also be involved in studying environmental conditions in which the firm operates, competitor behaviour, or other data sources. Requires knowledge of tools and methods including statistics, artificial intelligence and machine learning. OML Roles mapped to this profile are: Specialist Data Scientist.

Responsibilities

Advanced and Predictive Analytics

Create well-defined backlog and prioritised road maps that align predictive analytics projects with business needs, leading cross-functional teams in the implementation and ongoing use of advanced and predictive analytics' software tools and functionalities.

Model Creation and Maintenance

Responsible for the maintainance of complex models, ensuring that the underlying assumptions are fully researched and validated and that the models can be integrated into wider business models to enable analysis, reporting, and compliance.

Data Exploration

Perform complex statistical analysis and utilize mining, modeling, and testing techniques to enable data analysis. Experiment with different hypotheses using test and learn methodologies.

Data and Analytics Strategy

Plan all business and technical aspects of different data and analytics systems and platforms. Understand features and properties, ensure data integrity of new and existing tracking, and own the maintenance and administrative functions of these models and data science artifacts.

Performance Improvement through Business Intelligence

Create complex algorithms that identify patterns in unstructured and structured data through data. Manage data preparation in collaboration with different stakeholders/internal clients in the business. Responsible for commerical value articulation of the models.

Data Architecture

Implement all aspects of data architecture, turning event analytics, raw application data, and business systems into key business insights.

Data Collection and Analysis

Use data from a wide range of sources to analyze key themes and identify possible impacts on the business. Create end to end solutions which include problem defintiion, data acquisition, data exploration and visualisation.

Business Requirements Identification

Proactively elicit complex business requirements using a variety of methods such as interviews, document analysis, workshops, and workflow analysis to express the requirements in terms of target user roles and goals.

Insights and Reporting

Contribute to the design and creation of reporting strategies and templates. Lead execution of complex reports, identifying and interpreting complex patterns and trends, and translating those insights into actionable recommendations. Turn data into actionable insights that answer the business pain points identified by telling a succient story with the data. Communicate key insights to business in an effective and easy to understand manner.

Personal Capability Building

Act as subject matter expert in an area of technology, policy, regulation, or operational management for the team. Maintain external accreditations and in-depth understanding of current and emerging external regulation and industry best practices through continuing professional development, attending conferences, and reading specialist media. Coaches and mentors data scientists in the areas of machine learning, statistical analysis and predictive models.

Skills

Action Planning, Business Requirements Analysis, Computer Literacy, Data Compilation, Data Controls, Data Management, Executing Plans, IT Architecture, IT Network Security, Policies & Procedures

Competencies

Business Insight

Cultivates Innovation

Drives Results

Manages Ambiguity

Manages Complexity

Plans and Aligns

Situational Adaptability

Strategic Mindset

Education

NQF Level 7 - Degree, Advance Diploma or Postgraduate Certificate or equivalent

Closing Date

30 April 2025 , 23:59

The appointment will be made from the designated group in line with the Employment Equity Plan of Old Mutual South Africa and the specific business unit in question.

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