Data Scientist

Role overview

This is a remote, United States-based Data Scientist role with a partner employer that handles the application review and follow-up process. The position sits in a fast-moving, product-focused setting where data science helps shape customer experience and overall business performance at scale.

In this role, you will build and operationalize machine learning solutions that support personalization, search, and recommendation capabilities for a global audience. The work blends advanced statistical analysis, Python development, and cloud-based technologies to solve meaningful real-world problems. You will partner with product and engineering teams to turn complex datasets into practical insights and production-ready systems, with a strong focus on measurable impact and end-to-end ownership.

Responsibilities

• Create, deploy, and maintain machine learning models that improve personalization, search relevance, and recommendation quality.
• Develop data-driven algorithms that raise user engagement and conversion performance.
• Use statistical techniques and data mining methods to uncover patterns in large datasets.
• Work with engineering and product stakeholders to integrate ML solutions into live systems with strong scalability and reliability.
• Track model behavior over time and refine approaches using production data and business feedback.
• Convert business challenges into analytical and ML approaches that influence core KPIs.
• Support scalable ML operations through cloud infrastructure and data pipelines.
• Contribute to experimentation design and A/B testing to measure model effectiveness.

Requirements

• At least 2 years of experience in a Data Scientist, Quantitative Analyst, Quantitative Researcher, or similar analytical position.
• Strong working knowledge of Python and common data science libraries such as pandas, NumPy, and scikit-learn.
• Excellent grounding in probability, statistics, machine learning, and linear algebra.
• Demonstrated success applying ML to real business problems with measurable effect on revenue or key metrics.
• Solid SQL skills and experience using relational databases.
• Exposure to cloud platforms such as AWS, GCP, or Microsoft Azure is highly preferred.
• Comfort with productionizing ML models and building end-to-end data science workflows.
• Ability to thrive in a fast-paced, product-led environment with cross-functional teams.
• Clear communication skills with the ability to explain technical topics to non-technical audiences.
• Bachelor’s or Master’s degree in Applied Mathematics, Computer Science, Engineering, Financial Engineering, or another quantitative discipline.
• Using AI tools or agents in the development workflow is an added advantage.
• Apache Spark experience and/or gaming industry exposure is considered a plus.

Perks and benefits

• Remote-first setup with flexible work arrangements.
• Competitive compensation plus quarterly performance-based bonuses.
• 28 days of paid annual leave.
• Flexible schedule with core working hours between 10:00 am and 3:00 pm local time.
• High-end equipment provided for work use.
• Annual company retreats for collaboration and networking.
• Referral and performance-linked bonus programs.
• Opportunity to work on large-scale ML systems that directly affect business outcomes.
• Strong focus on professional development and exposure to modern ML and cloud tools.

Additional information

This role is published on behalf of a partner company, which will manage applications and the next steps in the hiring process.

The hiring partner uses an AI-supported matching process to review applications quickly, consistently, and fairly against the role’s core requirements. The shortlist is then shared with the employer, while interviews and assessments are handled by the employer’s internal team.

By submitting an application, candidates acknowledge that their personal data will be processed for recruitment evaluation and shared with the hiring employer where relevant. This processing is based on legitimate interest and pre-contractual steps under applicable data protection laws, including GDPR. Candidates may request access, correction, deletion, objection, and other applicable rights at any time.

The hiring process may include AI tools to support application review, resume analysis, response assessment, and basic verification signals. These tools assist the recruitment team and do not replace human judgment; final hiring decisions are made by people. Additional details on data handling can be requested from the employer.