C2C Job opportunity for Lead Data Scientist Portland, OR

Role: Lead Data Scientist
Location: Portland, OR
Duration: Long Term

Job Description:
 

This role will be responsible for using predictive analytics and advanced optimization techniques—including mathematical programming, operations research, and industrial organization economics—to forecast consumer demand, enhance decision making, and drive action against our strategic priorities.

Specifically, you will:

Develop and implement advanced optimization models (e.g., linear, nonlinear, integer programming) to solve complex business problems in pricing, product allocation, inventory management, and supply chain design.
Apply principles from industrial organization economics to analyze market structure, competitive dynamics, and consumer behavior, informing strategic decisions.
Collaborate with business stakeholders to translate operational challenges into mathematical models and optimization frameworks.
Evaluate and integrate cutting-edge optimization solvers and technologies into analytics ecosystem.
Lead initiatives to improve efficiency and effectiveness of resource allocation using quantitative optimization methods. Identify and apply methods to acquire, explore, cleanse, and fuse data from different sources.
Design, write, own and maintain production grade analytics code to support forecasting and/or optimization models. Review and ensure code quality of peers.
Assess business requirements and constraints to make trade-off recommendations between speed and accuracy of alternative solution approaches.
Be a key contributor to building, scoring, deploying, monitoring, updating and promoting central forecasting platform.
Facilitate the planning, scheduling and value measurement of the work to meet timeline targets and success criteria.
Support the adoption of analytic products through effective storytelling and collaboration with key partners.
Participate in a continuous learning environment within the advanced analytics community through persistent development of new skills and sharing of knowledge through mentorships and contributions to the open source community.
Advanced degree (PhD or Master’s preferred) in Operations Research, Industrial Organization, Applied Mathematics, Statistics, Economics, Computer Science, or related field and at least 5 years of related industry experience or Bachelor’s degree and 7-12 years related industry experience.
Demonstrated expertise in mathematical optimization (e.g., linear programming, mixed-integer programming, stochastic optimization) and experience with commercial or open-source solvers (e.g., Gurobi, CPLEX, CBC, Pyomo).
Strong background in industrial organization economics, including market analysis, pricing strategies, and competitive modeling.
Experience applying optimization and economic theory to real-world business problems, preferably in retail, supply chain, or consumer goods sectors.
Advanced programming skills in Python and optimization libraries (e.g., PuLP, Pyomo, OR-Tools), with ability to build and maintain production-grade optimization software.
Proven ability to communicate complex optimization concepts and results to non-technical stakeholders.
Demonstrated ability to apply programming skills to data acquisition, preprocessing, modeling and monitoring as well as familiarity with the wide range of data science/analytics software tools.
Experience with common data science/analytics software tools (e.g. Jupyter Notebook, SQL, Spark, Git) and cloud computing platforms (e.g. Amazon Web Services).
Experience in building, training, scoring, tuning and maintaining predictive models in production at enterprise scale and familiarity with mainstream packages relevant to managing all stages of Data Science/Analytics lifecycle.