Data Scientist

We are looking for a talented and driven Data Scientist to join our team. In this role, you will be a significant and autonomous contributor, delivering end-to-end machine learning solutions and major analytical initiatives that directly drive business value. You will work across model development, experimental design, and data workflows — solving difficult data science problems with pragmatic, scalable solutions that make a real difference to the business.

Responsibilities

Design, build, and deploy production-grade machine learning models and analytical solutions that are robust, scalable, and maintainable by other data scientists.; Apply a broad range of statistical methods and ML algorithms, using sound judgment on when — and when not — to use them.; Write highly performant, well-documented, and reproducible code in Python and SQL.; Collaborate with product managers, business stakeholders, and engineering teams to clarify requirements, scope analytical work, and deliver on project milestones.; Make thoughtful trade-offs between model performance and interpretability, complexity and simplicity, and computational cost and accuracy.; Identify and resolve data quality issues and analytical gaps; drive improvements to data science workflows and model reliability.; Actively contribute to model reviews, experimental design discussions, team planning, and post-deployment performance evaluations.; Work to find and address root causes of model performance issues, leaving systems better than you found them.; Contribute to on-call support and take ownership of issues, driving resolutions or ensuring clear handoffs.; Automate manual reporting tasks and contribute to operational excellence across the team.; Mentor junior data scientists and actively participate in the hiring and interview process.

Requirements

3+ years of hands-on Data Science experience. A formal degree is not required if you have equivalent knowledge gained from experience.; Strong proficiency in Python for statistical programming and machine learning development.; Expertise writing high-performance SQL queries and working with large-scale datasets.; Solid understanding of a broad range of statistical methods and machine learning algorithms.; Demonstrated ability to independently deliver end-to-end model development — from problem definition through production deployment.; Ability to build solutions that are pragmatic, consider business constraints, and can be maintained and extended by others.; Experience working with data visualization tools and communicating analytical findings clearly to non-technical stakeholders.; Strong sense of ownership — you document your work thoroughly, validate it rigorously, and ensure quality at every step.; Collaborative mindset with the ability to work across teams, balance competing requirements, and influence peers constructively.

Nice to have

Experience with MLOps practices, model monitoring, or automated reporting pipelines.; Familiarity with experimental design and A/B testing frameworks.; Track record of improving team workflows, data documentation practices, or analytical infrastructure.; Experience mentoring junior data scientists or contributing to onboarding and training programs.; Experience classifying, storing, and handling data in accordance with data governance policies.; Experience with distributed computing and big data technologies such as Apache Spark.; Experience with data visualization tools such as Tableau.; Experience working with cloud data warehouses such as Amazon Redshift or Google BigQuery.; Experience working with high volume and high velocity data in a distributed environment.