Tiger Analytics is a global AI and analytics consulting firm. With data and technology at the core of our solutions, our 4000+ tribe is solving problems that eventually impact the lives of millions globally. Our culture is modeled around expertise and respect with a team first mindset.

Headquartered in Silicon Valley, you?ll find our delivery centers across the globe and offices in multiple cities across India, the US, UK, Canada, and Singapore, including a substantial remote global workforce. We?re Great Place to Work-Certified?. Working at Tiger Analytics, you?ll be at the heart of an AI revolution.

You?ll work with teams that push the boundaries of what is possible and build solutions that energize and inspire. Tiger?s growing Banking Financial Services vertical seeks self-motivated AI/ML/Data Science professionals with domain expertise in the Banking and Financial Services space and strong technical skills for a challenging role in the Banking &

- Financial Services Analytics area.

About the Role: This role is for a highly analytical and detail-oriented individual to join our Banking and Financial Services Team. This role will play a crucial role in leveraging data to understand customer behavior, product performance, and market trends within retail and commercial banking, ultimately driving strategic decisions and enhancing the overall portfolio .

Key Responsibilities: 1. Data Extraction &

- Analysis: ? Extract, manipulate, and analyze large datasets using tools like Python, PySpark, SQL, ? Develop and maintain data models, dashboards, and reports to monitor key performance indicators (KPIs) related to banking and financial products (e.g., acquisition, activation, portfolio monitoring, usage, retention, profitability, risk). ? Perform in-depth ad-hoc analysis to identify trends, opportunities, and areas for improvement across the banking and financial product lifecycle, P&L; (revenue and cost components). This could be in Retail or Commercial Banking Domains. 2.

Insight

Generation &

- Storytelling: ? Translate complex data findings into clear, concise,



and actionable insights and recommendations for product managers, senior leadership, and cross-functional teams. ? Develop compelling presentations and narratives to communicate insights effectively, articulating the "why" behind the data. ? Identify customer needs, behaviors, and pain points through data analysis to inform product enhancements and new feature development. 3.

Product Performance

Monitoring &

- Optimization: ? Track and analyze the performance of existing banking and financial products, identifying drivers of success and areas of underperformance . ? Support the development and evaluation of business cases for current product initiatives, features, and pricing strategies. ? Collaborate with marketing, sales, risk, operations, and technology teams to implement data-driven product strategies and campaigns. ? Monitor competitive landscape and market trends to identify opportunities for product innovation and differentiation. ?

Thought

Leadership from a Banking and Financial Services (focus on Credit Bureaus) standpoint on product and data monetization strategies 4.

Model

Development, Validation &

- Risk Analytics: ? Work closely with risk teams to develop, validate, and monitor analytical models (e.g., credit risk, fraud, marketing) ? Analyze banking portfolio risk, identify potential issues, and support the development of risk mitigation strategies. ? Ensure all analytical activities comply with relevant regulatory requirements and internal policies. 5.

Process Improvement: ? Continuously seek opportunities to improve data collection, analysis, and reporting processes. ? Automate reporting and analytical tasks where possible to increase efficiency, using industry standard Automation Tools.

Required

Qualifications,



Capabilities and Skills: Experience: ? Proven experience (3-8 years) in data analytics and/or data science role, specifically within the banking and financial services industry (Retail and Commercial Banking). ? Prior experience with credit bureaus is highly preferred. ? Hands-on experience with data extraction and manipulation using Python, PySpark, or SQL. ? Familiarity with banking and financial product lifecycle, key metrics, and industry best practices Skills: ?

Strong

Analytical &

- Problem-Solving Skills: Ability to interpret complex data, identify patterns, and draw meaningful conclusions. Excellent critical thinking and logical reasoning. ?

Technical Proficiency: Advanced proficiency in Python, PySpark, and SQL is essential. ? Knowledge of advanced statistical modeling or machine learning techniques. ?

Data Visualization: Ability to create clear, compelling, and informative data visualizations using tools like Tableau (highly desirable) ?

Business Acumen: Solid understanding of banking and financial services business models, profitability drivers, and customer segments ?

Communication: Excellent written and verbal communication skills, with the ability to articulate complex analytical findings to both technical and non-technical audiences. ?

Collaboration: Ability to work effectively in a cross-functional team environment. ? Proactive &

- Self Motivated: A self-starter who can take initiative, manage multiple projects, and drive them to completion with minimal supervision. ?

Attention to Detail: Meticulous approach to data accuracy and analysis.

Good to have: ? Familiarity with AWS environment is a strong plus. ? Familiarity with AWS and GEN-AI/ Agentic AI Use Cases is preferred. ? Familiarity with financial regulations pertaining to banking and financial services is preferred.

Education: ? Bachelor's degree in quantitative fields such as Finance, Economics, Statistics, Mathematics, Computer Science, or a related discipline. ? A master?s degree is a plus. Looking for Tier 1 colleges / business schools

📌 Model Development - BFS (E) (Bengaluru)
🏢 Tiger Analytics
📍 Bengaluru