Lead Data Scientist - Merchandising & Pricing @DICK'S Sporting Goods
Data Analysis
Salary usd 95,200 - 15..
Remote Location
πŸ‡ΊπŸ‡Έ USA Only
Job Type full-time
Posted 2d ago

[Hiring] Lead Data Scientist - Merchandising & Pricing @DICK'S Sporting Goods

2d ago - DICK'S Sporting Goods is hiring a remote Lead Data Scientist - Merchandising & Pricing. πŸ’Έ Salary: usd 95,200 - 158,800 per year πŸ“Location: USA

Role Description

As the Lead Data Scientist - Merchandising & Pricing , you will be a key technical leader in our teammate transformation that aims to deliver a best-in-class teammate experience by providing them advanced intelligent decisioning tools using AI/GenAI and Machine Learning at its core. This is an exceptional opportunity not only to transform the way we deliver omnichannel Merchandising and Pricing by building foundational AI/GenAI capabilities, but also to do career defining work in the space.

This role will require an emerging technical leader & SME with strong experience in traditional Machine Learning algorithms along with deep understanding of the cutting edge SOTA AI/GenAI methods used in Retail merchandising and Pricing data science initiatives. As a technical leader you will be influencing critical enterprise technical strategies both in the Machine Learning/AI space and neighboring spaces like forecasting, optimization, NLP, webservices, integrations with applications and data systems etc. You will partner with product, business, and engineering leads to design and implement data science powered intelligent tools for merchandising and pricing business partners and scale and help them understand the art of the possible with AI technology through deep technical design.

Responsibilities

  • Lead design and implementation of advanced data science algorithms that improve merchandising and pricing business decisions, including building models for:
    • Demand forecasting
    • Assortment optimization
    • Price elasticity
    • Inventory allocation and replenishment
  • Designing and deploying demand forecasting algorithms that go beyond univariate time series to multivariate and hierarchical forecasts for predicting long range, multi-echelon sales forecasting.
  • Develop & Implement AI/ML driven assortment selection algorithms that learn from user behavior & preferences.
  • Collaborate with product & data engineers to identify data for modeling, and transform datasets as required for effective modeling.
  • Build, scale and deploy robust Machine Learning models leveraging Classification, Regression, and Clustering techniques.
  • Develop models to process historical and large datasets to understand model Price elastic demand for products.
  • Collaborate with analytics, product and business teams to champion a test-and-learn approach by designing and executing structured experiments.
  • Staying updated with the latest advancements in AI, ML technologies and exploring opportunities to incorporate these innovations into Merchandising and Pricing transformation initiatives.

Qualifications

  • Master's Degree or Equivalent Level in quantitative fields like computer science, engineering, physics, mathematics, etc.
  • 6+ years of experience in the field with at least 2-3 years of being the main technical lead in related projects.
  • Experience working with SOTA machine learning, deep learning (LSTM, Transformers), Optimization models for retail and ecommerce use cases.
  • Experience with Large Language models and Generative AI and Agents.
  • Experience in ML Ops model monitoring, retraining, CI/CD, and experiment tracking.
  • Extensive experience using common machine learning and deep learning frameworks such as TensorFlow, PyTorch, OpenAI, and LangChain.
  • Expert understanding of Python and other common languages.
  • Expert level experience in cloud platforms like Databricks, GCP, and offers like Azure ML, Vertex AI.
  • Experience being the technical lead of multiple projects at the same time.
  • Experience in an Agile working environment and at least one related project management tool (Azure, DevOps, Jira, etc.).
  • Previous experience mentoring, training, and developing junior members of the team through technical influence.
  • Experience with software engineering principles as it relates to Machine Learning systems.
  • Comfortable presenting results to and influencing senior and executive leadership on strategic technical decisions.
  • Brings a collaborative, problem solving and growth mindset to all interactions with a strong focus on delivery.

Requirements

  • Master's Degree or equivalent level preferred.
  • Substantial general work experience together with comprehensive job related experience in own area of expertise to fully competent level. (Over 6 years to 10 years).

Benefits

  • Targeted Pay Range: $95,200.00 - $158,800.00.
  • Competitive total rewards package that could include other components such as: incentive, equity and benefits.
  • Generous suite of benefits.

Virtual Requirements

At DICK’S, we thrive on innovation and authenticity. To protect the integrity and security of our hiring process, we ask that candidates do not use AI tools during interviews or assessments. Please note the following:

  • Cameras must be on during all virtual interviews.
  • AI tools are not permitted to be used by the candidate during any part of the interview process.
  • Offers are contingent upon a satisfactory background check which may include ID verification.
Before You Apply
️
πŸ‡ΊπŸ‡Έ Be aware of the location restriction for this remote position: USA Only
β€Ό Beware of scams! When applying for jobs, you should NEVER have to pay anything. Learn more.
Lead Data Scientist - Merchandising & Pricing @DICK'S Sporting Goods
Data Analysis
Salary usd 95,200 - 15..
Remote Location
πŸ‡ΊπŸ‡Έ USA Only
Job Type full-time
Posted 2d ago
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️
πŸ‡ΊπŸ‡Έ Be aware of the location restriction for this remote position: USA Only
β€Ό Beware of scams! When applying for jobs, you should NEVER have to pay anything. Learn more.
Apply for this position
Did not apply βœ“
Applied βœ“
Sent Follow-Up βœ“
Interview Scheduled βœ“
Interview Completed βœ“
Offer Accepted βœ“
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