Sr. Data Scientist – Fintech
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Salary
≈ $21k – $46k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Senior
Confirmed on the employer's own hiring board on Oct 31, 2026. First seen by Alion on Oct 28, 2026.
Overview
Company
Impact
Profile match
TeamPlus Staffing Solution, also known as Team Plus India, is an IT staffing and recruitment firm based in Pune that provides staff augmentation, contract and temporary staffing, contract-to-hire, permanent and executive placement, offshore staffing and recruitment process outsourcing. It recruits for client companies across Indian technology hubs including Bengaluru, Pune, Chennai, Hyderabad, Noida, Gurgaon and Kochi, and also markets AI engineering talent to overseas clients. Its listings are mostly client vacancies for data engineers, AWS cloud support engineers, DevOps and QA engineers, .NET and SAP ABAP developers, PCB and Creo design engineers and BI engineers.
Experience
8+ Years
Industry
Fintech / Card Payments / Retail Banking
We are seeking an experienced Sr. Data Scientist with strong expertise in Card Payments / Retail Banking, Machine Learning, and end-to-end analytics project delivery.
The candidate will drive analytics-driven strategies, develop scalable machine learning solutions, and deliver actionable business insights for banking and payments clients.
Key Responsibilities
- Lead and deliver end-to-end data science and analytics projects.
- Develop and implement machine learning models for banking and payment analytics.
- Drive credit card portfolio strategies using customer, transaction, and third-party data.
- Perform data cleaning, wrangling, feature engineering, feature selection, and predictive modelling.
- Define project scope, analytical methodologies, and solution frameworks.
- Translate complex analytical findings into actionable business recommendations.
- Collaborate with business stakeholders and clients to identify analytics opportunities.
- Explore new data sources, advanced modelling techniques, and innovative analytical solutions.
- Present insights through effective data storytelling and business presentations.
Mandatory Skills
- Domain Experience: Hands-on experience in Credit Cards, Card Payments, or Retail Banking.
- Machine Learning: Linear Regression, Logistic Regression, Decision Trees, Random Forest and predictive modelling.
- Programming: Strong hands-on experience in Python and SQL.
- Big Data / Analytics: Experience with PySpark, Hadoop, Hive, or similar technologies.
- End-to-End Data Science: Data preparation, feature engineering, model development, validation, deployment and scaling.
- Business Analytics: Experience developing analytical strategies and delivering measurable business outcomes.
- Communication: Strong presentation, stakeholder management and data storytelling skills.
Preferred Skills
- Credit card portfolio analytics and customer behaviour analysis.
- Payment transaction analytics and financial services data.
- Tableau, MS Excel and PowerPoint.
- Experience handling multiple client-facing analytics projects.
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