Manager – BI Analytics & Data Science

Job Purpose

The Manager – BI Analytics & Data Science drives data-driven decision-making by building end-to-end analytical solutions. The role bridges the gap between raw data and business strategy by managing the full lifecycle of data—from pipeline engineering and ETL to advanced predictive modeling and high-impact Power BI visualizations.

Key Responsibilities

1. Data Engineering & Advanced Analytics

• Streamline ETL processes and develop optimized data models to drive efficient, high-performance Power BI reporting and advanced analytical insights.
• Develop and deploy Machine Learning models and statistical frameworks to solve complex business problems.
• Utilize SQL, Python, or R to perform deep-dive analysis and identify predictive trends.
• Maintain the integrity and performance of the data architecture supporting analytics.

2. Power BI Visualization & Reporting

• Lead the design and maintenance of interactive Power BI dashboards and automated reporting tools.
• Translate complex datasets into clear, visual stories that allow stakeholders to track KPIs in real-time.
• Utilize Advanced Excel for specialized data manipulation, ad-hoc analysis, and complex financial modeling.
• Communicate technical findings to non-technical stakeholders to guide strategic growth.

3. Governance & Strategy

• Align data initiatives with cross-functional business goals while ensuring compliance with data governance and security policies.

Required Qualifications & Experience

• Education: Bachelor’s or Master’s degree in Data Science, Computer Science, or Statistics.
• Experience: 4–5 years in BI and Data Science.
• Industry Preference: Prior experience in the Banking or Financial Services sector is highly preferred and will be a significant plus point .
• Technical Stack: Expertise in Power BI , SQL , and Advanced Excel , with strong proficiency in Python/R , ETL development , and data modeling .
• Expertise: Hands-on experience in Machine Learning , statistical analysis, and creating advanced DAX measures .
• Banking Domain: Banking knowledge or past experience in banking is a plus, specifically regarding credit risk, deposits, branchless banking, or financial regulatory requirements.
• Soft Skills: Sharp analytical thinking and the ability to present data insights clearly to leadership.