Overview:

We’re looking for a Senior Data Scientist to lead the development and deployment of advanced machine learning models that power critical business decisions. In this role, you’ll drive end-to-end ownership of ML solutions, from design and optimization to deployment and monitoring in production environments. You’ll also play a key role in shaping our data science strategy, mentoring junior team members, and ensuring that analytics insights translate into measurable business impact. This is a high-visibility role where your expertise will directly influence product innovation and growth.

Role & Responsibilities:

Model Development and Optimization:
Lead the design, development, and deployment of advanced ML models for complex use cases, such as recommendation systems, fraud detection, customer segmentation, and demand forecasting.
Partner with data engineers and product teams to ensure models are scalable, reliable, and aligned with business needs.
Continuously optimize algorithms for performance, accuracy, and efficiency.
Deployment and Integration:
Own end-to-end model deployment processes into production environments using Kubernetes and cloud platforms (AWS, GCP).
Define and manage MLOps best practices, including model monitoring, automated retraining, and CI/CD for ML pipelines.
Champion automation of model training, validation, and deployment workflows to improve system reliability.
Analytics Strategy & Enablement:
Act as a custodian of organizational data, ensuring data quality, consistency, and readiness for advanced analytics and modeling.
Translate complex data insights into business impact, clearly communicating ROI to stakeholders.
Drive adoption of analytics and data-driven decision-making across teams by mentoring and enabling business stakeholders.
Leadership & Collaboration:
Mentor junior data scientists and analysts, providing technical guidance and career development support.
Collaborate closely with engineering and product leadership to shape the company’s data science strategy.
Stay ahead of emerging AI/ML trends, tools, and research, and advocate for their adoption when relevant.

Requirements:

Proficiency in Python and SQL, with hands-on expertise in ML frameworks such as TensorFlow, PyTorch, Scikit-learn.
Strong knowledge of deployment tools (Docker, Kubernetes, cloud platforms) and MLOps best practices.
Proven ability to design and maintain production-grade ML systems.
Deep understanding of statistical analysis, hypothesis testing, and data visualization.
Knowledge of cloud-serverless technologies (AWS Lambda, GCP Functions, Azure Functions).
Strong familiarity with GCP is a plus.
Prior experience deploying ML solutions in E-commerce or high-growth environments is highly desirable.
Familiarity to work with Git and GitHub.
Dataform is a must

Experience:

5+ years in data science, including hands-on ML model development and deployment.
3+ years in data analytics, statistical modeling, and experimentation.
Experience mentoring or leading junior data scientists.
Exposure to fast-scaling startup or tech environments is a strong plus