Insight Global
Overview
A large global retailer in the Northwest Arkansas area is looking for a Principal Data Scientist – Forecasting, Optimization & Causal Inference.
Responsibilities
Define the research and technical strategy for forecasting, causal inference, and optimization across multiple product areas.
Architect end-to-end forecast–optimize–evaluate pipelines that drive strategic initiatives in pricing, supply chain, marketing, and finance.
Lead development of next-gen time series and optimization systems, integrating scenario simulation, causal reasoning, and robust policy evaluation.
Champion causal ML frameworks (structural causal models, counterfactual analysis, do-calculus, Bayesian causal inference) in live decision systems.
Guide applied optimization research — from classical operations research (MILP, stochastic programming) to modern RL-based control.
Mentor staff-level scientists, set long-term technical direction, and scale data science best practices across teams.
Partner with executives to ensure DS research influences multi-year business strategy.
We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment without regard to race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com. To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.
Qualifications
Master's degree or PhD in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 7 years' experience in analytics related field.
Recognized expertise in time series forecasting, optimization, and causal inference, with a proven record of delivering systems at scale.
Experience in transformer-based sequence models and PEFT methods for efficient large-model adaptation.
Deep background in mathematical optimization, Bayesian methods, and causal inference.
Track record of mentoring staff and senior DS, guiding research pipelines, and cross-org technical leadership.
Strong communication skills to bridge technical depth with business impact. Academic or open-source contributions in forecasting, causal inference, or optimization.
Experience integrating optimization + causal inference + forecasting pipelines in enterprise systems.
Background in economics, operations research, or applied mathematics.
Leadership experience on cross-functional strategy-setting initiatives.
Represent the organization externally through conference presentations (NeurIPS, ICML, ICLR), collaborations with academia, or whitepapers.
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Responsibilities
Define the research and technical strategy for forecasting, causal inference, and optimization across multiple product areas.
Architect end-to-end forecast–optimize–evaluate pipelines that drive strategic initiatives in pricing, supply chain, marketing, and finance.
Lead development of next-gen time series and optimization systems, integrating scenario simulation, causal reasoning, and robust policy evaluation.
Champion causal ML frameworks (structural causal models, counterfactual analysis, do-calculus, Bayesian causal inference) in live decision systems.
Guide applied optimization research — from classical operations research (MILP, stochastic programming) to modern RL-based control.
Mentor staff-level scientists, set long-term technical direction, and scale data science best practices across teams.
Partner with executives to ensure DS research influences multi-year business strategy.
We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment without regard to race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com. To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.
Qualifications
Master's degree or PhD in Statistics, Economics, Analytics, Mathematics, Computer Science, Information Technology or related field and 7 years' experience in analytics related field.
Recognized expertise in time series forecasting, optimization, and causal inference, with a proven record of delivering systems at scale.
Experience in transformer-based sequence models and PEFT methods for efficient large-model adaptation.
Deep background in mathematical optimization, Bayesian methods, and causal inference.
Track record of mentoring staff and senior DS, guiding research pipelines, and cross-org technical leadership.
Strong communication skills to bridge technical depth with business impact. Academic or open-source contributions in forecasting, causal inference, or optimization.
Experience integrating optimization + causal inference + forecasting pipelines in enterprise systems.
Background in economics, operations research, or applied mathematics.
Leadership experience on cross-functional strategy-setting initiatives.
Represent the organization externally through conference presentations (NeurIPS, ICML, ICLR), collaborations with academia, or whitepapers.
#J-18808-Ljbffr