Lets Write Africa's Story Together!

Old Mutual is a firm believer in the African opportunity and our diverse talent reflects this.

Job Description

Data Science & Analytics Specialist who will play a critical role in safeguarding our organization against fraud and financial crime. This position is ideal for a highly analytical and tech-savvy professional with 1–2 years of experience, who is passionate about using data to uncover risks, identify anomalies, and deliver proactive fraud detection solutions.

In this role, you’ll work at the intersection of data science, analytics, and forensic investigation, helping us detect fraud risks early and enhance integrity across our banking and insurance operations.

1. Key Tasks and Responsibilities

Develop and deploy data-driven models and BI dashboards for early fraud detection and behavioral pattern analysis 

Conduct proactive forensic data analysis using advanced tools such as Alteryx, IDEA, Power BI, and Tableau

Write and optimize SQL, Python, and R scripts to query structured/unstructured data for anomalies and indicators of potential fraud

Support investigations by extracting, cleaning, and transforming large volumes of financial, claims, and transactional data 

Build repeatable analytics workflows to monitor risk indicators across key business functions

Work closely with internal audit, risk, compliance, and IT teams to improve fraud detection strategies

Contribute to data governance and data quality initiatives supporting forensic integrity and regulatory reporting

2. Skills and Competencies

Languages/Scripting: SQL, Python, R

Analytics & BI Tools: Power BI, Tableau, IDEA, Alteryx (Altrexy)

Data Science & Engineering: ETL workflows, data wrangling, feature engineering

Excel: Advanced data analysis and visualizationStrong understanding of fraud typologies in the banking and insurance sectors

Ability to translate complex datasets into actionable forensic insights 

3. Knowledge and Experience

Familiarity with fraud detection models (e.g., outlier detection, clustering, anomaly scoring)

Exposure to case management tools and forensic investigation platforms

Experience with regulatory frameworks like AML, FATCA, or fraud compliance in financial services

Knowledge of internal audit or forensic procedures is beneficial

4. Qualifications

Bachelor’s degree in computer science, Information Technology, Data Science, or related field

1–2 years of experience in data analytics, business intelligence, or data science

Certifications preferred: 

Power BI Certification

Certified Data Management (CDM) or equivalent

Experience or exposure to data governance and data quality frameworks is an advantage

Prior work in financial services, especially in banking, insurance, or fraud risk functions, is a strong plus 

.

Skills

Action Planning, Claims Management, Data Compilation, Data Controls, Executing Plans, Financial Auditing, Insurance Claims Investigations, Typology

Competencies

Action OrientedBusiness InsightCollaboratesDecision QualityEnsures AccountabilityFinancial AcumenInstills TrustManages Complexity

Education

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

Closing Date

28 August 2025 , 23:59

The Old Mutual Story!