Data Scientist - Pricing & Product Strategy

October 15

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Dealer Tire

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automotive • tires • maintenance • distribution • program management

1001 - 5000

💰 $157.9M Private Equity Round on 2009-09

Description

• Manage Large Datasets • Dive deep into data—utilize programming tools to cleanse, validate, and ensure the quality of large structured and unstructured data sets • Apply transformation techniques (e.g., missing data, standardizing formats, detecting outliers, duplicate data) to move data from its raw form into clean, high-quality data tables • Use SQL and data APIs to interact with data stored in various systems from relational databases to file systems • When necessary, apply machine learning or other applicable techniques to enhance usefulness and reliability of large data sets • Collect and curate data needed for research, from both internal and external sources • Iteratively, efficiently, and effectively identify and execute projects that provide significant value to the organization focusing on a measurable impact. • Develop mathematic models that allow the organization to maximize service and minimize costs • Apply statistical and algorithmic methods such as supervised machine-learning, unsupervised machine-learning, hypothesis testing, regression analysis, forecasting, natural language processing, clustering, classification, survival analysis, simulations and optimizations • Communicate findings through clear, visual presentations that can be easily consumed by staff and executives, making complex analyses understandable to technical and nontechnical stakeholders. • Provide data-driven insight—draw valid conclusions and make recommendations • Serve as key contributor and developer for assigned projects and help coordinate activities of team • Ensure project sponsors are consistently kept up to date on project status • Initiate discussions on potential projects by identifying opportunities for data-driven solutions that can address business challenges or improve operations. • Mentor team members and participate in discussions to support internal documentation efforts to help maintain accessible and organized project knowledge for the team.

Requirements

• Master’s degree in Mathematics, Computer Science, Engineering or other quantitative fields • 2-5 years of experience • Ability to present complex technical material to executive audiences • Proficient with project management and product management skill sets • Works with a sense of urgency and is able to work independently with minimal supervision • Proficiency in MS Office (Excel, Word, Power Point) • Advanced proficiency in programming languages for statistics and automation (Python) • Proficient in data-access languages (SQL, PostgreSQL, T-SQL) • Experience with Alteryx • Experience with Amazon Web Services (AWS) • Proficient with version control approaches for product development (Unit testing, Git, documentation, logging, etc.) • Proficient in statistical modeling, supervised and unsupervised machine-learning frameworks (SciPy, Caret, sklearn) • Familiarity with container services (Rancher, Kubernetes, Docker) is a plus • Familiarity with OBIEE, Salesforce or Google Analytics platforms is a plus

Benefits

• Paid time off • Medical • Dental • Vision • 401k match (50% on the dollar up to 7% of employee contribution)