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Brand: Corporate

Role: Data Scientist II - eComm Relevance (REMOTE)

Location: United States

City, State: Remote

Job Area: Full time

Job ID: 202404575

Job Category: Technology

Data Scientist II - eComm Relevance (REMOTE)

At DICK’S Sporting Goods, we believe in how positively sports can change lives. On our team, everyone plays a critical role in creating confidence and excitement by personally equipping all athletes to achieve their dreams. We are committed to creating an inclusive and diverse workforce, reflecting the communities we serve.

If you are ready to make a difference as part of the world’s greatest sports team, apply to join our team today!


At DICK’S Sporting Goods, we take a people-centric approach to everything we do. Our Athletes, how we refer to customers, and our Teammates, how we refer to our employees, are at the center of every decision we make so that we can provide transformational experiences online, in store, and in sport. When you join Technology at DICK’S Sporting Goods, you’re joining a true team that wins together. We help our Athletes and fellow Teammates better their best by innovating solutions to interesting business problems and empowering every Technology Teammate to be an innovator. And, while we work remotely from all over the United States, we provide virtual and in-person events for the team to hangout, from virtual escape rooms to cheering on the Pittsburgh Pirates at beautiful PNC Park.


Build machine learning models that will enable DSG to improve products, solutions and business outcomes. Study product and process-related data, may also be involved in studying environmental conditions, competitor behavior, or other data sources. Leverage some advanced knowledge of tools and methods including statistics, artificial intelligence and machine learning; knowledge of coding practices including source control. Begins to translate business questions into data science solutions with some supervision. Learn to manage own projects and communicate effectively with business and technical stakeholders. Learns to deploy work automations in a technical manner.

  • Data-driven Product and Service Improvement: Research data from digital product/service performance, customer behavior, and market trends to identify opportunities for product/service improvement

  • Advanced and Predictive Analytics: Employ machine learning techniques and perform advanced and predictive analyses and perform model assessments, validation, and enhancement activities, using predictive analytics' software tools and functionalities

  • Advanced Data Collection and Analysis: Conduct advanced research using primary data sources and select information needed for the analysis of key themes and trends

  • Data Exploration: Conduct research and select relevant information to enable analysis of key themes and trends using primary data sources, statistical analysis, and modeling techniques

  • Data and Analytics Strategy: Make recommendations to improve data and analytics systems and platforms, contributing to the continuous improvement and refinement of data and analytics strategy

  • Performance Improvement through Business Intelligence: Create basic machine learning algorithms and support creation of more complex algorithms that identify patterns in structured data. Support the collection of data in accordance with model standards

  • Data Architecture: Consult and educate stakeholders on methods for streamlining and standardizing data recording to ensure quality and accuracy.

  • Functional/Technical Requirements: Support collection of functional requirements using document analysis and workflow analysis to express requirements clearly and succinctly

  • Machine Learning Operations: Use source control systems and write prod supportable code. Learn to deploy machine learning models within a machine learning platform. Research machine learning libraries, models, algorithms, and train/retrain systems. Support model experiments and testing.

  • Horizon Scanning: Explore and develop a detailed understanding of external developments or emerging issues and contribute to the evaluation of their potential impact on, or usefulness to, the organization.

  • Ongoing Learning and Development: Develop own capabilities by participating in assessment and development planning activities as well as formal and informal training and coaching; gain or maintain external professional accreditation where relevant to improve performance and fulfill personal potential. Maintain an understanding of relevant technology, external regulation, and industry best practices through ongoing education, attending conferences, and reading specialist media


  • Bachelor's Degree or equivalent level preferred

  • General Experience: Experienced practitioner able to work unsupervised (13 months to 3 years)

Targeted Pay Range: $76,500 - $124,600. This is part of a competitive total rewards package that could include other components such as: incentive, equity and benefits. Individual pay is determined by a number of factors including experience, location, internal pay equity, and other relevant business considerations. We review all teammate pay regularly to ensure competitive and equitable pay. We also offer a generous suite of benefits. To learn more, visit
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