Data Science and Analytics Specialist at Old Mutual Kenya

Job Description

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
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
​​​​​​​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
​​​​​​​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