Fictiv Exists to Enable Hardware Innovators to Build Better Products, Faster. This role aims to identify and solve complex business challenges using data to improve efficiency, scalability, and profitability across operations, supply chain, finance, product, and engineering.
Requirements
- Hands-on experience with machine learning algorithms (e.g., regression, classification, clustering, forecasting, reinforcement learning) and model evaluation frameworks
- Hands-on experience preparing and curating datasets for machine learning or AI research, including cleaning, transformation, labeling, and creation of synthetic or anonymized data for model training or simulation purposes
- Demonstrated experience in experimental design, hypothesis testing, and A/B test evaluation, with a clear understanding of sampling, control groups, and significance testing in applied business contexts
- Demonstrated expertise in Python (pandas, numpy, scikit-learn, etc.) and SQL, with the ability to design efficient data pipelines and feature engineering workflows
- Strong background in data exploration, feature engineering, and model validation, with the ability to design experiments and evaluate model performance rigorously
- Demonstrated skill in developing and operationalizing ML-driven solutions that enhance business workflows while ensuring models are interpretable and scalable
- Experience working with modern data platforms such as Snowflake, Fivetran, or dbt, and integrating models into BI or operational systems (e.g., Sigma, Tableau, Power BI)
Responsibilities
- Lead the scoping, planning, and delivery of high-impact data science projects that address complex business challenges across pricing, supply chain, scheduling, and manufacturing operations
- Design, develop, and deploy predictive and prescriptive models that enable smarter decision-making, improve forecasting accuracy, and drive automation across business workflows
- Partner with the AI Research Group to prototype and implement AI-driven solutions to improve workflow efficiency, including intelligent pricing systems, predictive maintenance, and process automation
- Prepare, clean, and transform complex datasets to support advanced modeling and AI initiatives, including generating synthetic, anonymized, or simulated data as needed to train or validate machine learning and reinforcement learning systems
- Collaborate with Data Engineering to ensure high-quality, reliable data pipelines and feature sets that support advanced analytics and model development
- Work closely with product managers and engineering teams to integrate data science capabilities into Fictiv’s digital platform and operational tools
- Document modeling approaches, assumptions, and methodologies to ensure reproducibility and transparency of results
Other
- This role is based in our Oakland, CA office, with 2-3 days per week required in the office
- Partner with stakeholders across Operations, Supply Chain, Finance, Product, and Engineering to define problems, explore opportunities for optimization, and design data science solutions
- Mentor peers, contribute to the development of shared methodologies, and help establish standards for modeling, experimentation, and data quality across the organization
- Communicate results clearly and effectively to both technical and non-technical stakeholders, providing actionable insights and recommendations that influence strategic decisions
- Thrive in a collaborative environment — open to feedback, discussion, and iteration in pursuit of the best solutions
