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Remote Demand Forecasting Jobs (NOW HIRING)

Ferrellgas

Supply Analyst

Kansas City, MO · Remote

At Ferrellgas our corporate roles are fully remote, enabling talented professionals to support our ... Support demand forecasting activities by analyzing business trends, customer needs, inventory ...

FNA

Supply Analyst

Kansas City, MO · On-site +1

Overview At Ferrellgas our corporate roles are fully remote, enabling talented professionals to ... Support demand forecasting activities by analyzing business trends, customer needs, inventory ...

Advatix, Inc.

Demand Planning Lead

Seattle, WA · On-site +1

$80K - $90K/yr

Seattle, Washington preferred but open to remote Compensation: $80,000 to $90,000 Role Summary As a ... Deliver proposed order analytics that inform forecasting, sourcing, and inventory decisions.

Advatix, Inc.

Demand Planning Lead

Seattle, WA · Remote

Seattle, Washington preferred but open to remote Compensation: $80,000 to $90,000 Role Summary As a ... Deliver proposed order analytics that inform forecasting, sourcing, and inventory decisions.

CSC Generation

Remote -- US or Canada \\n About the Role As our Staff Data Scientist , you will design and ship production pricing systems such as demand forecasting, price elasticity modeling, dynamic pricing and ...

Donaldson Company, Inc.

Planner II

Chillicothe, MO · On-site +1

Oversees advanced planning functions, including long-term demand forecasting and capacity planning ... International relocation or remote work arrangements outside of the U.S. will not be considered.

Ancient Crunch Inc

Demand Planning Associate

$60K - $80K/yr

Remote Direct Reports: None anticipated, though direct reports may be added or removed based on ... Conduct monthly forecast review cycles in partnership with Sales, Marketing and Supply Chain ...

Danaher

Global Commercial Demand Planning Director

Austin, TX · On-site +1

$180K - $220K/yr

The primary location for this role is US-Remote , and the position will be fully remote, with the ... Apply Danaher Business System principles to improve forecast accuracy, reduce bias and volatility ...

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How much do remote demand forecasting jobs pay per year?

As of Jul 22, 2026, the average yearly pay for remote demand forecasting in the United States is $82,760.00, according to ZipRecruiter salary data. Most workers in this role earn between $65,000.00 and $96,000.00 per year, depending on experience, location, and employer.

How does a remote demand forecasting specialist typically collaborate with cross-functional teams to improve forecast accuracy?

As a remote demand forecasting specialist, collaboration with cross-functional teams such as sales, marketing, supply chain, and finance is essential to enhance the accuracy of forecasts. This is usually achieved through regular virtual meetings, shared data dashboards, and collaborative forecasting tools that allow for transparent communication and timely updates. Building strong relationships and maintaining open channels for feedback helps ensure that all relevant market trends, promotions, and external factors are considered in the forecasting process. Effective communication skills and proactivity in seeking input from various departments are key to success in this remote role.

What are the key skills and qualifications needed to thrive in Remote Demand Forecasting, and why are they important?

To thrive in Remote Demand Forecasting, you need strong analytical skills, a solid understanding of statistics and data analysis, and typically a degree in business, mathematics, or a related field. Proficiency in forecasting software (such as SAP IBP, Oracle Demantra, or Microsoft Excel), data visualization tools, and sometimes certifications in supply chain or analytics are common requirements. Excellent communication, attention to detail, and problem-solving abilities help you interpret data trends and collaborate effectively with cross-functional teams. These skills and qualifications are essential for producing accurate forecasts, optimizing inventory, and supporting informed business decisions in a remote environment.

What is remote demand forecasting?

Remote demand forecasting is the process of predicting future customer demand for products or services using statistical analysis, machine learning, and historical data, all done from a remote location. Professionals in this field use specialized software and tools to collect and analyze data, create forecasting models, and communicate findings to stakeholders without being physically present at a company’s office. This approach allows organizations to make informed decisions about inventory, staffing, and production while leveraging remote talent and technology.
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What cities are hiring for Remote Demand Forecasting jobs? Cities with the most Remote Demand Forecasting job openings:
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Remote Demand Forecasting jobs near you
Infographic showing various Remote Demand Forecasting job openings in the United States as of July 2026, with employment types broken down into 55% Full Time, 41% Part Time, and 4% Contract. Highlights an 65% Physical, 1% Hybrid, and 34% Remote job distribution, with an average salary of $82,760 per year, or $39.8 per hour.
Lead Data Scientist - Merchandising & Pricing (REMOTE)

Lead Data Scientist - Merchandising & Pricing (REMOTE)

Dick's Sporting Goods

Remote

Full-time

PTO

Posted 21 days ago

Dick's Sporting Goods rating

6.5

Company rating: 6.5 out of 10

Based on 1,145 frontline employees who took The Breakroom Quiz

15th of 39 rated national retailers

Job description

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!
OVERVIEW:
Are you a passionate technologist with experience in AI, Machine Learning, Data Science and Analysis? Are you looking for an opportunity to drive enterprise impact and shape the future of a leading sports retailer with $12B+ in revenue and 800+ physical stores? Do you enjoy working with a highly skilled team of Machine Learning engineers & Scientists, co-creating enterprise grade AI capabilities?
JOB PURPOSE:
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:
  • Advanced Data Science Leadership: 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, and Inventory allocation and replenishment.

  • Developing & Optimizing Demand Forecasting models: 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, and that can handle cold start problems, reconciliation at all levels and works at scale.

  • Assortment Planning & Optimization: Develop & Implement AI/ML driven assortment selection algorithms that learn from user behavior & preferences to deliver tailored assortment choices based on user metadata like location, past site behavior etc. and that are optimized for the capacity, variety, sales targets and other business constraints.

  • Natural Language Process (NLP) & GenAI: Collaborate with product & data engineers to identify data for modeling, and transform datasets as required for effective modeling, like creating identifying and enriching product attributes using NLP and LLMs. Creating feature stores and vector embedding used for Product associations and segmentation, and other modeling needs.

  • Machine Learning & Deep Learning: Build, scale and deploy robust Machine Learning models leveraging Classification, Regression, and Clustering, Context understanding, techniques to drive data-driven decision-making across diverse retail business functions. Leverage deep learning models for building complex forecasting and other predictive use cases.

  • Price Elasticity & Casual Inference: Develop models to process historical and large datasets to understand model Price elastic demand for products, categories, channels and customer segments using predictive and causal modeling techniques. Deliver actionable elasticity estimates and counterfactual analyses to inform pricing optimization, promotional strategies, and markdown decisions to monitor the performance of forecasting and other predictive models in real time, detect anomalies, ensuring data drift, concept drift, and addressing technical issues to maintain the efficiency & effectiveness of model predictions.

  • Experimentation & A/B Testing: Collaborate with analytics, product and business teams to champion a test-and-learn approach by designing and executing structured experiments to validate model hypotheses, measure business impact, and drive continuous improvement.

  • Research & Development of Emerging Technologies: Staying updated with the latest advancements in AI, ML technologies and exploring opportunities to incorporate these innovations into Merchandising and Pricing transformation initiatives.

PREFERRED 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 driving efficiency in operations and customer value.
  • Experience with Large Language models and Generative AI and Agents. Bonus if specific experience in operations research.
  • 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, responsible for delivery and business metrics
  • 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, from the lens of science.
  • Brings a collaborative, problem solving and growth mindset to all interactions with a strong focus on delivery.

QUALIFICATIONS:
  • Education: Master's Degree or equivalent level preferred
  • General Experience: 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)

#LI-FD1
VIRTUAL REQUIREMENTS:
At DICK'S, we thrive on innovation and authenticity. That said, to protect the integrity and security of our hiring process, we ask that candidates do not use AI tools (like ChatGPT or others) during interviews or assessments.
To ensure a smooth and secure experience, please note the following:
  • Cameras must be on during all virtual interviews.
  • AI tools are not permitted to be used by the candidateduring any part of the interview process.
  • Offers are contingent upon a satisfactory background check which may include ID verification.

If you have any questions or need accommodations, we're here to help. Thanks for helping us keep the process fair and secure for everyone!
Targeted Pay Range: $95,200.00 - $158,800.00. 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.DICK'S Sporting Goods complies with all state paid leave requirements. We also offer a generous suite of benefits. To learn more, visit www.benefityourliferesources.com.

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