Senior Data Scientist

We are seeking a Senior Data Scientist who thrives at the intersection of data, business, and technology. In this role, you will design, build, and deploy advanced machine learning models, uncover insights from complex datasets, and directly influence strategic decisions. You’ll collaborate with cross-functional teams, lead data-driven projects, and play a key role in scaling data science capabilities across the organization.

Key Responsibilities

• Model Development: Design, train, and deploy machine learning and statistical models to solve complex business problems.
• Data Strategy: Drive experimentation, data exploration, and innovative approaches to extract actionable insights.
• Feature Engineering & Pipelines: Build robust data pipelines and feature stores for scalable model deployment.
• Business Partnering: Translate business challenges into data science problems and communicate insights to non-technical stakeholders.
• Tooling & Infrastructure: Work with engineering teams to ensure models are production-ready, scalable, and monitored.
• Mentorship: Guide junior data scientists and analysts, sharing best practices in ML, experimentation, and coding standards.
• Continuous Improvement: Stay ahead of advancements in ML/AI research, tools, and frameworks, and bring cutting-edge approaches into practice.

What We’re Looking For

• 6–10 years of experience in data science / machine learning roles, with hands-on exposure to end-to-end ML lifecycle.
• Strong proficiency in Python / R, SQL, and ML frameworks (TensorFlow, PyTorch, Scikit-learn, XGBoost, etc.).
• Experience in data wrangling, large-scale data analysis, and distributed systems (Spark, Hadoop, etc.).
• Solid grounding in statistics, probability, optimization, and algorithms.
• Track record of delivering measurable business impact through data science solutions.
• Strong communication skills to explain technical findings to non-technical teams.
• Master’s/PhD in Computer Science, Statistics, Applied Mathematics, or related field preferred.