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Lead Data Scientist

Job in Navi Mumbai, India
Listing for: Dynamic Yield
Full Time position
Listed on 2026-03-06
Job specializations:
  • IT/Tech
    Machine Learning/ ML Engineer, Data Scientist, AI Engineer, Data Analyst
Salary/Wage Range or Industry Benchmark: 800000 INR Yearly INR 800000.00 YEAR
Job Description & How to Apply Below
Our Data Science and Analytics team is seeking a  Lead Data Scientist  who is passionate about leveraging data to deliver high-quality customer solutions. This team drives innovation across Intelligent Decisioning, Financial Certainty, Attribute, Feature, and Entity Resolution, Verification Solutions, and much more.
We are looking for a strong technical leader who is highly motivated, intellectually curious, analytical, and possesses an entrepreneurial mindset. Join us to make a significant impact across all sectors of the economy through consistent innovation and problem-solving.

The Role  As a Lead Data Scientist, you will:
Team Leadership & Growth:  Lead, mentor, and foster the growth of the data science team, while also evolving our data science tech stack, focusing on developing production-grade services and capabilities.
Project Planning & Direction:  Plan and direct data science and machine learning projects within the team, from conception to deployment.
Model Design & Implementation:  Design and implement cutting-edge machine learning models for a variety of financial applications, including but not limited to:
Transaction Classification, Temporal Analysis, and Risk modeling from both structured and unstructured data.
Model Performance & Improvement:  Measure, validate, implement, monitor, and continuously improve the performance of both internal and external-facing machine learning models.
Innovative Problem Solving:  Propose creative and novel solutions to existing challenges, pushing the boundaries within the company, the financial industry, and the field of data science.
Communication:  Clearly and succinctly present complex technical problems and findings to business leaders internally and to clients. You'll be a strong, confident, and excellent writer and speaker, capable of effectively communicating your vision and roadmap to a wide variety of stakeholders.
Scalable Solutions:  Leverage best practices in machine learning and data engineering to develop robust and scalable solutions.
Resource Optimization:  Identify areas where resources fall short of needs and provide thoughtful, sustainable solutions to benefit the team and enhance efficiency.
All About You

Experience:

8+ years of experience  in data science and machine learning model development and deployments.
Domain Knowledge (Plus):  Exposure to financial transactional structured and unstructured data, transaction classification, risk evaluation, and credit risk modeling is a plus.
Technical Proficiency:  A strong understanding of  NLP (Natural Language Processing), Statistical Modeling, Visualization , and advanced Data Science techniques/methods.
Text Analysis:  Ability to gain insights from text, including non-language tokens, and apply thought processes of annotations in text analysis.
Problem-Solving:  Proven ability to solve problems that are new to the company, the financial industry, and to data science.
Database

Skills:

SQL / Database experience  is preferred.
Deployment

Experience:

Experience with  Kubernetes, Containers, Docker, REST APIs, Event Streams , or other delivery mechanisms.
Relevant Technologies:  Familiarity with relevant technologies (e.g.,  Tensor Flow, Python, scikit-learn, Pandas , etc.).

Collaboration:

Strong desire to collaborate and ability to develop creative solutions.
Industry Experience (Preferred):  Additional Finance and Fin Tech experience is preferred.

Education:

Bachelor's or Master's Degree in Computer Science, Information Technology, Engineering, Mathematics, Statistics, with an M.S. preferred.
Corporate Security Responsibility  Every person working for, or on behalf of, Mastercard, is responsible for information security. All activities involving access to Mastercard assets, information, and networks come with an inherent risk to the organization. Therefore, it is expected that the successful candidate for this position must:
Abide by Mastercard's security policies and practices.
Ensure the confidentiality and integrity of the information being accessed.
Report any suspected information security violation or breach.
Complete all periodic mandatory security trainings in accordance with Mastercard's guidelines.
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