Senior Data Scientist

About the Role

We are seeking a Senior Data Scientist to design, build, and scale advanced machine learning solutions that power customer engagement, optimization, and decision-making systems. This role is ideal for someone who enjoys translating complex business challenges into robust, production-ready data products and thrives at the intersection of machine learning, software engineering, and data platform development.

You will take deep ownership of the end-to-end ML lifecycle, from model design and experimentation to deployment, monitoring, and continuous improvement. Beyond model development, you will play a critical role in building reliable data foundations, ensuring engineering excellence, and driving scalable solutions that deliver measurable business impact.

Key Responsibilities

Develop Advanced Machine Learning Solutions

• Design, train, evaluate, and deploy machine learning models to solve business problems across customer behavior, prediction, segmentation, recommendation, optimization, forecasting, and related domains.
• Translate business requirements into practical and scalable data science solutions.
• Select appropriate algorithms, features, and evaluation methodologies to maximize model performance and business value.

Build and Maintain Data & ML Infrastructure

• Architect and develop scalable data pipelines supporting both structured and unstructured data workloads.
• Design data models, schemas, and transformation frameworks that enable reliable machine learning operations.
• Integrate new data sources, manage backfills, and optimize pipeline performance, scalability, and cost efficiency.

Ensure Model Reliability and Production Readiness

• Establish rigorous validation, monitoring, and quality-control processes throughout the model lifecycle.
• Detect and mitigate issues such as data quality degradation, drift, bias, and operational edge cases.
• Implement automated testing and governance practices to maintain high standards of reliability and reproducibility.

Drive Engineering Excellence

• Write clean, maintainable, and production-grade Python and SQL code.
• Apply software engineering best practices including code reviews, testing, documentation, and CI/CD automation.
• Continuously improve platform health by reducing technical debt, streamlining workflows, and decommissioning obsolete assets.

Qualifications

• Bachelor's degree or higher in Computer Science, Statistics, Mathematics, Physics, Engineering, Data Science, or a related quantitative discipline.
• At least 4 to 6 years of hands-on experience building and deploying machine learning solutions in production environments.
• Strong proficiency in Python and SQL, with experience developing scalable data pipelines and data processing frameworks.
• Demonstrated experience working with large datasets and end-to-end machine learning workflows, from experimentation through deployment and monitoring.
• Strong understanding of statistical modeling, machine learning techniques, model validation methodologies, and data quality controls.
• Experience applying data science to customer analytics, personalization, recommendation systems, lifecycle management, growth optimization, or similar business domains is highly desirable.
• Strong problem-solving skills and the ability to operate independently in a fast-paced, highly technical environment.