Data Scientist (Fintech / Applied ML)

Job Description

About The RoleWe are seeking a highly analytical and technically proficient Data Scientist to join our fast-paced Fintech product team. You will leverage statistical analysis, machine learning, and potentially Generative AI to build impactful solutions that drive business outcomes, such as risk modeling, fraud detection, and predictive analytics.This is a high-ownership role where you will take responsibility for projects from initial problem scoping and data discovery through feature engineering, model building, validation, and final deployment into production systems. You will work closely with data engineers and analytics engineers to ensure the reliability of data pipelines feeding your ML workflows. We require candidates with a strong foundation in computer science, specifically from top-tier institutions, who are comfortable working in a modern, production-grade AI environment.Key ResponsibilitiesEnd-to-End Model DevelopmentModel Building: Design and develop sophisticated machine learning models for predictive analytics, fraud detection, and decisioning systems within the fintech domain. Production Deployment: Take full ownership of deploying models into production environments, ensuring they are scalable, robust, and deliver measurable business value. Performance Monitoring: Implement continuous learning systems for model evaluation, data refresh, and retraining to maintain high predictive accuracy in production. Data Pipeline & Infrastructure IntegrationCollaboration: Partner with Data Engineers to source, clean, validate, and integrate data pipelines that feed into ML workflows. Data Quality: Perform rigorous data analysis, preprocessing, and feature engineering to ensure high-quality input for model training. Big Data Analytics: Extract, transform, and analyze data from large data warehouses utilizing big data technologies. Cross-Functional Collaboration & ComplianceStakeholder Engagement: Translate complex, ambiguous business problems into concrete data science objectives and communicate insights effectively to drive action. Data Governance: Ensure all data handling and processing complies with internal standards and external financial regulations (e.g., DPDP 2023), maintaining strict data privacy. What We Are Looking ForEducation (Strict Requirement) Dual Degree: B.Tech M.Tech in Computer Science, OR Tier 1 B.Tech: A Bachelor of Technology (B.Tech) degree exclusively from a Tier-1 engineering institute in India. Recognized Tier-1 institutions include:IITs: (e.g., Madras, Delhi, Bombay, Kanpur, Kharagpur, Roorkee, Hyderabad, Guwahati). NITs: (e.g., Trichy, Surathkal, Warangal, Rourkela). IIITs: (e.g., Hyderabad, Bangalore, Delhi). Premier Institutes: BITS Pilani, Jadavpur University. Experience & SkillsExperience: 2 to 5 years of hands-on, proven experience in a Data Science, Applied ML, or Decision Science role, preferably within the Fintech or BFSI sector. Programming & Scripting: Expert-level proficiency in Python (for ML and data manipulation) and SQL (for writing efficient, complex queries). Machine Learning: Solid grounding in ML fundamentals, statistical modeling, hypothesis testing, and experience with frameworks like Scikit-Learn, TensorFlow, or PyTorch. Latest Tech Stack: Experience with modern data science environments (e.g., Jupyter, DSW), cloud platforms (AWS preferred), and MLOps tools (e.g., MLflow, Kubeflow, SageMaker). Bonus (Not Mandatory): Familiarity with integrating LLMs or Generative AI workflows (LangChain, OpenAI APIs) into production environments. What We OfferCompetitive Salary: Up to 30,00,000 LPA, based on interview performance and specific skill sets. Impactful Work: The opportunity to build core models that directly impact risk management and business revenue. Work Environment: Full-time, Work-from-Office setup in our modern Bangalore or Gurgaon locations to foster tight collaboration. Skills: data scientist,learning,models,engineers,analytics,data science,collaboration,machine learning,data,ml,fintech .

Keyskills :
learningengineersanalyticsdata sciencecollaborationmachine learningdatadata scientist