Lead Data Scientist

Lead Data Scientist role bridging advanced R&D with production delivery across Service & Delivery (S&D) and Research & Development (R&D) at COMPETERA LIMITED.

Responsibilities

• Own and maintain a clear Data Science vision and strategy for the organization.
• Shape the technical roadmap based on business needs , team capacity , and long-term strategy.
• Gradually scale the data science function as the company grows.
• Define the hiring profile, lead and mentor a cross-functional team of Data Scientists, and grow an R&D culture focused on scientific rigor and measurable business impact .
• Manage resources across both Delivery (S&D) and Research (R&D) squads.
• Act as the main bridge between R&D and S&D by translating business requirements into research tasks.
• Help teams convert complex prototypes into stable, production-ready solutions.
• Architect client solutions by selecting appropriate models and assortment strategies to solve specific business problems using the existing stack.
• Serve as a quality gatekeeper : conduct code reviews, verify A&B test designs , and ensure the team meets Definition of Done (DoD) .
• Drive key DS metrics including research-to-production time , experiment velocity , and overall quality of price recommendations .
• Communicate clearly with product managers, engineers, and occasionally clients to explain trade‑offs, present results, and align on next steps.
• Represent COMPETERA’s technology expertise to investors and partners during due diligence by articulating DS strategy, algorithm defensibility, and the technical roadmap.
• Engage directly with customers’ Data Science and Analytics teams, including PhD‑level experts, by explaining methodology, model assumptions, and performance results, and handling technical questions.
• Present complex model results and performance metrics to key stakeholders in a clear, concise, business-focused way.
• Support sales and pre‑sales with technical narratives demonstrating value in the pricing domain .
• Stay hands‑on as needed, including designing new experiments, addressing critical issues in the delivery pipeline, and prototyping new ideas.

Requirements

• Minimum 5+ years of experience in Data Science or a related field with a focus on delivering value to production.
• Strong Python and SQL skills; ability to write modular, readable code for experiments and prototypes.
• Familiarity with Databricks and Apache Spark .
• General familiarity with Data Mesh approach and ability to leverage best practices with data engineers.
• Solid mathematical background, preferably in a Computer Science-related field.
• Proficiency with scientific Python toolkit: NumPy , pandas , scikit-learn , and either Keras/TensorFlow or PyTorch .
• Deep understanding of statistical testing methodologies, especially A&B testing design.
• Familiarity with Time Series Forecasting approaches.
• At least 3 years working with tabular and mixed (multimodal) data.
• Expertise in Causal Inference ; background in Ecommerce/Retail is a strong plus.
• Upper-intermediate or higher English and strong public speaking skills.
• Focus on value delivered to users and the business, not only mathematical model behavior.
• Ability to translate complex technical concepts into business language for stakeholders.
• Ability to communicate professionally with PhD-level customer scientists during sales, pilot, and rollout.
• Own data requirements and build efficient processes for integration and data engineering, including data integration and validation requirements.
• Willingness to experiment, pivot, and make data-driven decisions in a dynamic environment.
• Proactively contribute ideas to the Product Backlog based on technical knowledge and capabilities.
• Entrepreneurial mindset and curiosity with a drive to continuously learn.

Technologies

• Python
• SQL
• Databricks
• Apache Spark
• NumPy
• pandas
• scikit-learn
• Keras
• TensorFlow
• PyTorch

Benefits

• Rich innovative software stack with freedom to choose suitable technologies.
• Remote-first ideology with flexibility to work from home or a suitable coworking space.
• Flexible working hours (start between 8 to 11 am ) and no time tracking systems.
• Regular performance and compensation reviews.
• Recurrent 1-1s and measurable OKRs.
• In-depth onboarding with a clear success track.
• COMPETERA covers 70% of training/course fees.
• 20 vacation days, 15 days off, and up to one week of paid Christmas holidays.
• 20 business days of sick leave.
• Partial medical insurance coverage.
• Reimbursement for coworking costs.

Location: San Mateo, CA (remote)

Experience: 5+ years