IDFC FIRST Bank is hiring for a fresher entry level Data Scientist role in India

Position:

• Data Scientist

• Role focused on fraud prevention, operational analytics, and machine learning-driven strategies

• Key contributor to the Fraud and Operational Analytics team within the bank’s Data & Analytics department

Company:

• IDFC FIRST Bank

• One of India’s fast-growing private sector banks

• Known for its focus on customer-centric banking, innovation, and advanced digital solutions

Location:

• Mumbai, Maharashtra, India

Job type:

• Full-time position

Job mode:

• Onsite

Job requisition id:

• P-188181

Years of experience:

• Open to freshers and early-career professionals

• 0 to 3 years of relevant work exposure considered

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Company Description

• IDFC FIRST Bank is a prominent name in the Indian banking sector with a strong reputation for customer-first principles.

• The bank was created with the vision of combining cutting-edge digital technologies with deep customer understanding.

• It provides a wide range of services including retail banking, business banking, credit services, and financial inclusion initiatives.

• Innovation is central to the bank’s growth strategy, with constant investment in advanced analytics, artificial intelligence, and technology platforms.

• The organization values integrity, transparency, and a collaborative culture where employees can experiment, grow, and build long-term careers.

• Its core belief is that growth happens when employees and customers are empowered to succeed together.

• With operations across multiple cities and a strong customer base, IDFC FIRST Bank continues to expand its footprint while staying committed to responsible banking.

• The bank has consistently positioned itself as an employer that promotes growth opportunities, mentorship, and exposure to some of the most pressing challenges in finance and data science.

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Profile Overview

• The position is designed for individuals passionate about applying data-driven techniques to real-world financial problems.

• The role sits within the Fraud & Operational Analytics team, a critical unit responsible for safeguarding the bank’s ecosystem from fraud risks and operational inefficiencies.

• Day-to-day responsibilities involve analyzing large volumes of structured and unstructured data to detect fraud patterns and operational bottlenecks.

• This includes the design and deployment of machine learning models, anomaly detection systems, and predictive algorithms.

• The candidate will be tasked with deriving actionable insights that not only prevent fraudulent activities but also improve customer experience by minimizing false positives and unnecessary delays.

• This role encourages exploration of both traditional and alternative data sources, expanding the scope of fraud detection and risk assessment.

• By working closely with business and risk teams, the analyst will provide customized analyses and strategic support.

• The bank is looking for self-starters who can scope open-ended problems, design solutions, and communicate findings clearly to both technical and non-technical stakeholders.

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Responsibilities

• Gather, clean, and interpret large datasets to uncover fraud-related patterns.

• Build and refine advanced machine learning models for fraud detection and prevention.

• Innovate with data-driven strategies to improve operational processes.

• Research and integrate alternate data sources to enhance fraud detection capabilities.

• Design model training pipelines and ensure they are efficient and scalable.

• Translate business challenges into structured analytical frameworks.

• Deliver customized reports and strategic insights to business and risk teams.

• Monitor performance metrics and suggest improvements to reduce operational costs and risks.

• Stay updated on the latest fraud detection techniques, statistical methodologies, and AI innovations.

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Functional and Technical Skills

• Strong knowledge of econometric, statistical, and machine learning methods.

• Proficiency in Python, SQL, Pandas, Numpy, Scikit-learn, and exposure to TensorFlow or PyTorch.

• Understanding of statistical concepts, including regression, classification, clustering, and anomaly detection.

• Familiarity with fraud evaluation metrics and performance measurement techniques.

• Ability to approach open-ended problems logically and develop actionable solutions.

• Comfort working with large and complex datasets across multiple platforms.

• Skills in data strategy, modeling, and experimental design.

• Knowledge of optimization techniques for model performance.

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Qualifications

• Undergraduate degree in fields such as Computer Science, Technology, Engineering, or Mathematics. Acceptable degrees include:

  • Bachelor of Science (B.Sc)

  • Bachelor of Technology (B.Tech)

  • Bachelor of Computer Applications (BCA)

• Postgraduate education preferred, with degrees such as:

  • Master of Science (M.Sc)

  • Master of Technology (M.Tech)

  • Master of Computer Applications (MCA)

• Academic background should demonstrate exposure to quantitative methods, data science concepts, and programming.

• Candidates should showcase a combination of analytical thinking and technical proficiency.

• Freshers and individuals with limited industry experience are encouraged to apply if they have strong foundational skills.

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Additional Info

• The role provides a unique opportunity to apply data science skills in a high-impact banking context.

• Candidates will gain experience in fraud risk management, operational analytics, and large-scale machine learning deployments.

• The environment is fast-paced, requiring adaptability and a willingness to experiment with new ideas.

• Collaboration across multiple departments, including risk, operations, and business strategy, ensures broad exposure to the banking ecosystem.

• The bank emphasizes learning and growth, encouraging employees to attend training programs, pursue certifications, and experiment with new technologies.

• A career in this role offers pathways to more senior positions in analytics, risk management, and data strategy.

• Employees are also expected to demonstrate professional conduct, integrity, and a commitment to the bank’s values.

• This position is ideal for individuals seeking to blend technical expertise with business problem-solving in a mission-critical area of the bank.

Please click here to apply.