Senior Data Analyst

Key Responsibilities:

Data Analysis & Insights

·         Lead advanced data analysis, including customer segmentation, portfolio analysis, risk behavior, and performance.

·         Develop analytical frameworks to identify business opportunities, operational gaps, and potential risks.

·         Perform deep-dive analysis to support strategic initiatives such as customer lifecycle optimization, acquisition strategy, and retention programs.

·         Conduct data exploration using large-scale datasets from multiple financial systems (e.g., loan management, credit scoring, push productivity).

Data Interpretation & Business Recommendations

·         Translate analytical findings into meaningful insights and clear business recommendations.

·         Create dashboards, reports, and executive summaries to guide decision-making.

·         Present insights to senior management and cross-functional teams such as Strategy, Marketing, Collections, Risk, and Sales.

·         Build models or analytical tools that enable non-technical stakeholders to understand key trends and make informed decisions.

Stakeholder Collaboration

·         Work closely with Strategy team to shape long-term business direction using data-driven insights.

·         Partner with Strategist, and User teams to define business requirements and convert them into analytical outputs.

·         Lead discussions to identify data needs and performance tracking mechanisms.

·         Support user teams in applying insights to improve workflow efficiency and business outcomes.

·         Review team outputs and ensure analytical quality meets business expectations.

Qualifications

·         Bachelor’s or Master’s degree in Data Science, Statistics, Economics, Finance, Business Analytics, Computer Science, or related fields.

·         Minimum 7 years of experience in data analysis within the financial industry (banking, lending, credit, fintech, financial service, insurance).

·         Proven experience in delivering deep insights and influencing strategic decisions at the management level.

·         Strong proficiency in analytical tools and languages (e.g., SQL, Python, Power BI/Tableau).

·         Experience working with financial datasets such as loan portfolios, credit scoring, customer behavior, or risk modeling.

·         Strong business acumen and ability to explain complex analysis in simple, actionable terms.

·         Excellent communication and presentation skills.

·         Experience managing or mentoring analysts is preferred.