Lead Data Scientist

Role & responsibilities

• Lead the design, development, and deployment of advanced machine learning and data science solutions.
• Translate complex business problems into data-driven solutions and actionable insights.
• Develop and optimize predictive models, statistical models, and AI/ML algorithms.
• Work with large and complex datasets to identify trends, patterns, and business opportunities.
• Lead end-to-end data science projects, from problem formulation and experimentation to production deployment.
• Collaborate with engineering, product, business, and analytics teams to deliver scalable solutions.
• Mentor and guide junior and mid-level data scientists and contribute to technical best practices.
• Design and evaluate experiments, A/B tests, and model performance metrics.
• Apply modern AI techniques, including deep learning, NLP, Generative AI, and LLM-based solutions where relevant.
• Establish best practices for model development, validation, deployment, monitoring, and MLOps.
• Present technical findings, model results, and business recommendations to senior stakeholders.
• Stay current with emerging developments in AI, machine learning, data science, and cloud technologies.

Preferred candidate profile

• 5 to 10 years of relevant experience in Data Science, Machine Learning, AI, or a related quantitative field.
• Strong proficiency in Python and SQL, with hands-on experience in machine learning and statistical modeling.
• Strong foundation in statistics, probability, machine learning, and experimental design.
• Experience building and deploying production-grade ML models and data products.
• Hands-on experience with deep learning, NLP, Generative AI, or LLMs is preferred.
• Experience with cloud platforms such as AWS, Azure, or GCP and modern data/ML platforms.
• Familiarity with MLOps tools and practices, including MLflow, Docker, CI/CD, model monitoring, and model deployment.
• Experience working with large-scale data using technologies such as Spark, Databricks, or equivalent platforms.
• Strong problem-solving, analytical, communication, and stakeholder-management skills.
• Demonstrated ability to lead projects independently and mentor other data scientists.
• Bachelors or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Economics, or another quantitative discipline.
• Strong business acumen with the ability to connect technical solutions to measurable business outcomes.