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.

Work arrangement
No