Data Scientist (6 to 8 Years)

Overview

Headquartered in India, its flagship product, the PhonePe digital payments app, was launched in Aug 2016. As of April 2025, PhonePe has over 60 Crore (600 Million) registered users and a digital payments acceptance network spread across over 4 Crore (40+ million) merchants. PhonePe also processes over 33 Crore (330+ Million) transactions daily with an Annualized Total Payment Value (TPV) of over INR 150 lakh crore.

PhonePe’s portfolio of businesses includes the distribution of financial products (Insurance, Lending, and Wealth) as well as new consumer tech businesses (Pincode - hyperlocal e-commerce and Indus AppStore Localized App Store for the Android ecosystem) in India, which are aligned with the company’s vision to offer every Indian an equal opportunity to accelerate their progress by unlocking the flow of money and access to services.

Culture:

At PhonePe, we go the extra mile to make sure you can bring your best self to work, Everyday!. And that starts with creating the right environment for you. We empower people and trust them to do the right thing. Here, you own your work from start to finish, right from day one. PhonePe-rs solve complex problems and execute quickly; often building frameworks from scratch. If you’re excited by the idea of building platforms that touch millions, ideating with some of the best minds in the country and executing on your dreams with purpose and speed, join us!

Job Description:

We are looking for an experienced Data Scientist with 6+ years of experience to join our team and drive impactful data-driven solutions. The ideal candidate will possess deep expertise in machine learning, statistical modeling, and big data processing, along with a proven ability to work with cross-functional teams and effectively communicate insights to stakeholders. This role requires a strategic mindset, strong leadership, and the ability to translate complex data problems into actionable business insights.

Key Responsibilities:

• Lead and drive the development of advanced machine learning models to solve high-impact business challenges.
• Collaborate with stakeholders (business leaders, product managers, engineering teams) to identify opportunities where data science can add business value.
• Embed yourself with business to understand the strategy and propose data solutions to accelerate outcomes.
• Design and implement scalable data pipelines and real-time analytics solutions.
• Guide and mentor data scientists, fostering a culture of innovation and best practices.
• Conduct deep-dive analyses to extract meaningful insights from complex and large datasets.
• Ensure machine learning models are explainable, reproducible, and aligned with business objectives.
• Present findings and recommendations to key stakeholders in a clear and actionable manner.
• Work closely with engineering teams to deploy ML models into production environments at scale.
• Own end-to-end model lifecycle management, including data preprocessing, feature engineering, model training, validation, and monitoring.
  
  

• Bachelor's or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field (Ph.D. preferred but not mandatory).
• 6+ years of experience in data science, machine learning, or applied statistics. Experience in financial services, fintech, e-commerce, or similar data-driven industries.
• Strong expertise in Python, SQL with proficiency in machine learning frameworks such as TensorFlow, PyTorch, or Scikit-Learn.
• Solid understanding of big data technologies (Spark, PySpark, Hadoop, or similar).
• Hands-on experience in model deployment using cloud platforms (AWS, GCP, Azure) and ML Ops frameworks (MLflow, Kubeflow, etc.).
• Expertise in statistical modeling, predictive analytics.
• Experience working with real-time and batch-processing systems.
• Demonstrated ability to translate business problems into data science solutions.
• Excellent problem-solving, critical-thinking, and analytical skills.
• Strong communication and stakeholder management skills, with the ability to explain technical concepts to non-technical audiences.
  
  

• Experience in financial services, fintech, e-commerce, or similar data-driven industries.
  
  

• Insurance Benefits - Medical Insurance, Critical Illness Insurance, Accidental Insurance, Life Insurance
• Wellness Program - Employee Assistance Program, Onsite Medical Center, Emergency Support System
• Parental Support - Maternity Benefit, Paternity Benefit Program, Adoption Assistance Program, Day-care Support Program
• Mobility Benefits - Relocation benefits, Transfer Support Policy, Travel Policy
• Retirement Benefits - Employee PF Contribution, Flexible PF Contribution, Gratuity, NPS, Leave Encashment
• Other Benefits - Higher Education Assistance, Car Lease, Salary Advance Policy