Location: Dallas, TX

This position will be Hybrid. 

This role will not support relocation. 

 

 

 

Summary:

This role within our Information Services department is looking for a Data Scientist that can apply scientific principles to analyze complex datasets across different groups to make business decisions. Develops scalable algorithms and models.​

 

Major Responsibilities: 

 

Translates well-structured business problems into data science problems. Analyzes complex datasets to inform or make decisions to address those business problems.​ Applies scientific principles and concepts to support invention. Uses a range of scientific methodologies and follows best practices for those methodologies.​ Proactively identifies solutions to problems. Solutions may require novel techniques or approaches.​ Creates metrics and measurements to quantify the business impact of the work.​ Writes accurate and clear technical documentation and reports, including appropriate mathematical rigor as needed.​ Communicates the approach and outcomes of models clearly and effectively with non-technical stakeholders to build trust.​ Collaborates with stakeholders across a broad set of functions (science, data, engineering, product, business).

 

Scope: 

Influence is primarily within the team ​ Deliver artifacts on medium size projects, define methodology and own analysis Results affect important business decisions.​ Influence teams technical and business strategy by making insightful contributions to team priorities and approach​ Develop metrics to quantify the benefits of a solution and influence project outcomes.

 

Qualifications:

Data analytics skills and experience analyzing both experimental and observational data sets​. Expertise in one or more of: machine learning, natural language processing, computer vision, operations research, applied mathematics, statistics, econometrics, causal analysis, or similar science discipline.​ Experience developing one or more of: A/B testing capabilities, forecasting models, inventory optimization, capacity planning, pricing, recommender systems, classification models, causal impact, customer choice models, or similar science products.​ Proficiency with math/stats software (e.g. R, Matlab, SAS, Stata, Python numpy) or other domain specific software (e.g. Python/TensorFlow for ML). Basic proficiency with SQL.​ Strong skills in model development, model validation, and model implementation. For ML-related roles, additional experience in model deployment and ongoing production support.

 

Experience and Education:

 

Masters/PhD in a quantitative field (CS, CE, ML, OR, Econ, or related). PhD preferred Minimum of 3 years of experience in data science or a related field​

 

 

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