Data Scientist, Supply Chain Analytics

Gymreapers
Nampa, ID, US
Full-time

Job Description

Job Description

Employment Status : Full-time, benefits eligible

Location : Perfereabley Nampa, ID (on-site); Open to Remote

Schedule : M-F, 8-5 / flex according to business needs

Compensation : Who We Are

Who We Are

Gymreapers is a direct-to-consumer e-commerce brand creating premium lifting gear, apparel, and equipment for men and women.

Our supportive lifting gear has been featured in Men’s Health, Barbend, Powerlifting Technique, and more. The Gymreapers brand has been listed twice on the Inc Magazine’s list of 5,000 fastest growing businesses : 2022 at #291 and 2021 at #521.

Our CEO, Roc Pilon, recently was named Entrepreneur of the Year by Ernst and Young!

Benefits / Perks

  • Competitive Pay
  • Paid Time Off (PTO)
  • Company paid holiday’s
  • 50% Employee Discount on Gymreapers.com!!
  • 100% Employer Paid : Medical, Dental and Vision, Short-term and Long-term disability, Life insurance for both employee and spouse / dependents
  • Health Savings Account (HSA) employee option

Job Summary :

Gymreapers is looking to add a Forecasting and Demand Planning professional to our powerful and fast-paced supply chain team.

Headquartered in Nampa, Idaho we work tirelessly to support our customers, athletes, and gym-goers on all fronts, all around the world.

In this role you will build, develop and implement the overall demand planning and forecasting strategy for the business.

This role will also offer query and reporting visualization expertise, supporting the business with live data correlated to company goals and key areas.

This is an exciting opportunity for anyone who enjoys creating a strategic vision, and being hands on in the execution of it.

Typical Duties and Responsibilities :

  • Develop reporting, analytics and models that support supply chain decisions through the creation of queries, visualization and dashboards
  • Establish a demand planning strategy with the intent to reduce stock outs on inventory through forecasting variance reduction and inaccuracy elimination
  • Be the subject matter expert around machine learning, statistical, and econometric time series techniques alongside hybrids of these to develop accurate, granular demand forecasts
  • Partner closely with Finance, Marketing, Sales, Procurement and Operations to develop data queries, reporting, and visualizations to assist with optimal buying decisions, and the mitigation of risks within the Supply Chain
  • Delivering and supporting production code driving business-critical decision-making systems.

Required Skills and Abilities :

Bachelors or Masters in a quantitative subject (i.e. computer science, economics, operations research, statistics, etc.

or a related field such as Industrial Engineering, Statistics, Mathematics, Computer Science, etc.

  • 3+ years of practical experience working in data science systems (ideally in e-commerce)
  • Experience delivering robust and maintainable production codebases that autonomously deliver data science models to downstream systems.
  • Experience in statistical / econometric time series modeling (ARIMA, Exponential Smoothing / ETS, GLMs / GAMs, Dynamic Factor Models, etc.

machine learning (XGBoost / LightGBM, RNNs, Transformers, etc.), or hybrid time series techniques (ES-RNN, N-BEATS, TFT).

  • Proficiency in Python, SQL, Git
  • Proficiency in using data visualization tools such as Tableau, or Bi-Reports
  • Passion for driving outsized business impact through applied science, humility, and collaboration.

Our Core Values

  • Grow or Die
  • Customer Obsession
  • Extreme Ownership
  • Nothing is Given / / Everything is Earned
  • Be Humble
  • 1% Better Everyday
  • Live with Integrity
  • Sacrifice

Gymreapers LLC is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, national or ethnic origin, disability, as well as any other characteristic protected by federal, provincial, or local law.

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30+ days ago
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