Data Scientist

Role & responsibilities

12:30 PM to 9:30 PM / Work from office / Gurgaon

Role overview:

As a Data Science Team Leader, you will lead a talented team of data scientists while maintaining hands-on involvement in complex technical projects. You will be responsible for recruiting, mentoring, and developing team members while ensuring the delivery of high-impact machine learning solutions for fraud detection and risk assessment.

Key Responsibilities:

Technical Leadership

• Define technical approaches for complex data science projects involving tabular data at scale
• Lead critical projects and contribute code to production systems
• Establish and maintain best practices for model development, evaluation, and deployment
• Conduct code reviews to ensure quality, maintainability, and adherence to standards
• Guide team members through complex technical challenges

Team Leadership & Management

• Recruit, onboard, mentor, and manage data scientists
• Foster a collaborative, innovative environment that encourages experimentation and knowledge sharing
• Work closely with data engineers, ML engineers, fraud domain experts, and product managers
• Define success metrics and demonstrate business value of data science initiatives
• Forecast team needs and advocate for necessary tools and infrastructure

Qualifications:

• M.Sc in Computer Science, Mathematics, Statistics, or a related field

• 6+ years of proven experience designing and implementing machine learning algorithms

  with tabular data and successfully deploying them to production

• 3+ years of experience managing and leading data science teams

  (minimum 3 direct reports)

• Demonstrated track record in recruiting, interviewing, and hiring data science talent

• Strong understanding and practical experience with various machine learning algorithms for structured/tabular data

• Strong programming skills with high standards for code quality - proficiency in Python

  with experience writing clean, maintainable, production-grade code
• Experience with data manipulation tools (e.g., Pandas, NumPy) to extract, clean, and transform large-scale tabular datasets
• Solid foundation in statistical concepts and techniques, including hypothesis testing, regression analysis, time series analysis, and experimental design

• Strong analytical and critical thinking skills to approach business problems

  and translate them into actionable solutions
• Demonstrated ability to lead cross-functional teams and contribute to a positive work environment
• Advantages
• Experience in the fraud domain -

  Strong advantage

• Experience with Airflow, CircleCI, PySpark, Docker and K8S

Preferred candidate profile