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Razorpay

Director - Machine Learning

Department
Engineering
Job Type / Location
Bengaluru
Experience Required
12+ years
Posted On

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.

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