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