Director - Machine Learning

About the Role

We are looking for an enthusiastic Director - Machine Learning to join our growing team. The hire will be responsible for working in collaboration with other data scientists and engineers across the organization to develop production-quality models for a variety of problems across Razorpay. Some possible problems include: making recommendations to merchants from Razorpay's suite of products, cost optimization of transactions for merchants, and automatic address disambiguation/correction to enable tracking customer purchases using advanced natural language processing techniques.

Responsibilities

• Develop and articulate a long-term vision for the data science function, aligning it with Razorpay's strategic goals to ensure impactful, business-oriented outcomes.
• Lead the effort to instill a data-driven mindset across the organization, championing the use of data science to make critical business decisions and maximize value.
• Lead and drive data science initiatives, providing strategic guidance and technical expertise to the team.
• Apply advanced data science methodologies, mathematics, and machine learning techniques to solve complex and strategic business problems.
• Collaborate closely with cross-functional teams, including engineers, product managers, and business stakeholders, to develop and deploy cutting-edge data science solutions.
• Oversee the integration of compliance and regulatory requirements into data science processes, ensuring models and analyses meet all necessary standards.
• Identify the right problems to solve for the organization with the highest ROI.
• Present findings, insights, and strategic recommendations to senior stakeholders, influencing key business decisions.
• Identify key metrics and develop executive-level dashboards to monitor performance and provide actionable insights.
• Oversee multiple projects simultaneously, ensuring high-quality deliverables within defined timelines.
• Mentor and guide junior data scientists, fostering their professional growth and promoting a culture of innovation and excellence.
• Continuously explore and implement advanced data science methodologies and emerging technologies to enhance solutions.
• Collaborate with research teams and stay updated with the latest advancements in the field of data science.

Requirements

• 12-15 years of experience in a data science role, with a proven track record of delivering impactful solutions and building and managing high-performance teams.
• Advanced degree (Master's or Ph. D.) in a quantitative field, such as Computer Science, Statistics, Mathematics, or related disciplines.
• Extensive expertise in advanced machine learning techniques, statistical analysis, and mathematical modeling.
• Mastery of programming languages such as Python, R, and Scala, with experience in building scalable and efficient data science workflows.
• ML-Engineering/ML-Ops knowledge, awareness, and proficiency of Kubernetes, NoSQL, Redis, etc.
• Vast experience with big data processing frameworks (e. g., Hadoop, Spark) and deep learning frameworks (e. g., TensorFlow, PyTorch).
• Strong leadership skills, with the ability to guide and inspire a team, prioritize tasks, and drive successful outcomes, excellent communication and presentation skills.
• Drive collaboration between data science, product management, and engineering teams to ensure alignment on project goals and seamless integration of machine learning solutions into products.
• Facilitate regular cross-functional meetings and workshops to identify key business challenges, drive data democratization, and brainstorm innovative and cost-effective solutions.
• Deep experience with cloud platforms (e. g., AWS, Azure, GCP) and their data science tools and services.
• A passion for continuous learning and staying up-to-date with the latest advancements in data science.
• Demonstrated ability to think strategically, solve complex problems, and deliver innovative solutions.