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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 Sciencerelated 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 811 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.

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