Lead Data Scientist

We are looking for an experienced and product-minded Lead Data Scientist to drive the evolution of our Data Science function, shape the technical vision, and guide a high-impact team working at the intersection of research and production. This is a unique opportunity to influence strategy, lead cross-functional teams, and build ML solutions that directly power mission-critical business decisions

What You Will Do

• Define and own the Data Science strategy, ensuring alignment with business goals and long-term product vision.
• Shape and maintain the technical roadmap based on business priorities, team capacity, and company growth.
• Scale the Data Science function as the organization expands, designing team structure and hiring profiles.
• Lead, hire, and mentor a cross-functional team of Data Scientists while fostering a strong R&D culture built on rigor and measurable impact.
• Manage resources across both Delivery (S&D) and Research (R&D) squads, ensuring clarity and productivity.
• Act as the bridge between R&D and Delivery: translate business needs into research tasks and adapt prototypes into production-ready solutions.
• Architect client solutions by selecting appropriate models, algorithms, and assortment strategies using our ML stack.
• Serve as the quality gatekeeper: review code, validate A/B test designs, and ensure all work meets the team’s Definition of Done (DoD).
• Drive key DS metrics such as research-to-production time, experiment velocity, and recommendation quality.
• Communicate insights clearly to product managers, engineers, clients, and stakeholders, aligning expectations and next steps.
• Represent the company’s technological excellence to investors and partners during high-stakes due diligence.
• Collaborate with clients' Data Science and Analytics teams (including PhDs), explaining methodology, assumptions, and results with confidence.
• Translate complex model outputs into concise, business-oriented presentations for executives and decision-makers.
• Support the sales and pre-sales process by building compelling technical narratives and showcasing ML capabilities.

• Stay hands-on when needed — from debugging critical delivery issues to prototyping new models or designing experiments.

   

What You Have

• 5+ years of experience in Data Science or a related field, with a strong record of delivering production value.
• Strong Python and SQL proficiency, with clean and modular coding practices.
• Hands-on experience with Databricks and Apache Spark.
• Familiarity with Data Mesh principles and collaboration workflows with data engineering teams.
• Solid mathematical foundation, ideally within a Computer Science–related discipline.
• Expertise in scientific Python tools: NumPy, pandas, scikit-learn, and either TensorFlow/Keras or PyTorch.
• Deep understanding of statistical methods and A/B testing frameworks.
• Experience with Time Series Forecasting approaches.
• 3+ years working with tabular and mixed (multimodal) data.
• Bonus: experience in Causal Inference and ecommerce/retail domains.

• Upper-intermediate or higher English proficiency and excellent public speaking skills.

   

Soft Skills

• A strong focus on business impact — understanding not only how the model works but why it matters.
• Ability to translate complex concepts into simple explanations for non-technical stakeholders.
• Professional communication with highly technical client teams, including PhD-level experts.
• Ownership of data requirements, integration workflows, and validation processes.
• Comfort with experimentation, iteration, and decision-making in a dynamic environment.
• Proactivity: contribute DS-driven ideas to the Product Backlog and influence roadmap direction.
• Creative thinking and a pragmatic approach to solving complex technical and product challenges.

• Curiosity, eagerness to learn, and a strong entrepreneurial mindset.

   

You Will Love Working With Us Because

• Innovative ML stack with freedom to choose the best tools and approaches.
• Remote-first culture with the flexibility to work from anywhere.
• Flexible working hours (start between 8–11 AM), no time tracking.
• Regular performance reviews and clear OKR structure.
• In-depth onboarding with transparent success milestones.
• We cover 70% of your training or course fees.
• 20 vacation days, 15 days off, and an additional week of paid Christmas holidays.
• 20 business days of paid sick leave.
• Partial medical insurance coverage.