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Assistant Data Scientist Forecasting Jobs (NOW HIRING)

Nestlé S.A.

Sr. Data Scientist (Forecasting)

Arlington, VA · On-site

$110K - $160K/yr

Join Nestlé IT & Digital as a Sr. Data Scientist supporting Nestlé USA Digital, whereyou'llpartner with the Supply Chain Planning team and the Analytics team to build the forecasting solutions that ...

Nestle

Sr. Data Scientist (Forecasting)

Arlington, VA · On-site

$110K - $160K/yr

... Data Scientist supporting Nestle USA Digital, where you'll partner with the Supply Chain Planning team and the Analytics team to build the forecasting solutions that power how Nestle USA plans and ...

CVS Health

Senior Data Scientist - Forecasting

$101K - $203K/yr

Build and extend the demand forecasting foundation behind CVS Retail's Unified Forecasting Platform ... Experience working with a data engineering/MLOpsteam to productionize data science models ...

Veho Tech, Inc.

Staff Data Scientist - Forecasting

$185K - $220K/yr

As a Staff Data Scientist for Forecasting, you will be the technical leader responsible for building and owning the sophisticated models that power Veho's Sales and Operations Planning (S&OP) process.

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How much do assistant data scientist forecasting jobs pay per year?

As of Sep 10, 2026, the average yearly pay for assistant data scientist forecasting in the United States is $165,018.00, according to ZipRecruiter salary data. Most workers in this role earn between $133,500.00 and $170,000.00 per year, depending on experience, location, and employer.

What does an assistant data scientist forecasting do?

An Assistant Data Scientist in Forecasting helps analyze historical data and uses statistical models or machine learning techniques to predict future trends or outcomes. Their tasks often include data cleaning, exploratory analysis, feature engineering, and supporting the development and validation of forecasting models. They work under the guidance of more experienced data scientists and may also help communicate results to stakeholders. This role is essential for businesses looking to make data-driven decisions about sales, inventory, demand, or other key metrics.

What are the key skills and qualifications needed to thrive as an assistant data scientist forecasting?

To thrive as an Assistant Data Scientist Forecasting, you need a solid foundation in statistics, data analysis, and forecasting methods, typically supported by a degree in a quantitative field such as mathematics, statistics, or computer science. Familiarity with tools like Python, R, SQL, and forecasting libraries (e.g., Prophet, ARIMA), as well as experience with data visualization platforms, is essential. Strong problem-solving skills, attention to detail, and effective communication help you interpret complex results and present actionable insights. These competencies are crucial to generate accurate forecasts that guide business decisions and drive organizational success.

What are some typical challenges assistant data scientists face when working on forecasting projects?

Assistant Data Scientists in forecasting often encounter challenges such as handling incomplete or noisy datasets, selecting appropriate modeling techniques, and tuning models for accuracy. They may also need to balance competing priorities between speed and precision, especially when deadlines are tight. Close collaboration with senior data scientists and domain experts is common, as it helps ensure that forecasts are both technically sound and aligned with business goals. Developing strong communication skills is essential for presenting complex findings to non-technical stakeholders.

What is the difference between Assistant Data Scientist Forecasting vs Data Scientist Forecasting?

AspectAssistant Data Scientist ForecastingData Scientist Forecasting
Required CredentialsBachelor's degree in Data Science, Statistics, or related field; some roles may prefer a master'sMaster's or PhD in Data Science, Statistics, or related field; strong programming skills
Work EnvironmentSupportive team, entry to mid-level projects, supervised tasksIndependent project work, complex analysis, strategic decision-making
Employer & Industry UsageTech companies, finance, retail, healthcare; entry to mid-level rolesResearch institutions, large corporations, specialized analytics teams

The Assistant Data Scientist Forecasting role typically involves supporting forecasting projects under supervision, focusing on data preparation and basic modeling. In contrast, a Data Scientist Forecasting leads complex forecasting models, interprets results, and influences strategic decisions. The roles differ mainly in experience level, scope of responsibilities, and independence.

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Assistant Data Scientist Forecasting jobs near you

Senior Data Scientist - Forecasting

Portland, OR • On-site

Tiger Analytics, LLC
Business Management Consulting • 201 - 500 employees
Learn more about Tiger Analytics, LLCexternal

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Re-posted 5 days ago

Job description

Tiger Analytics is looking for experienced Data Scientists to join our fast-growing advanced analytics consulting firm. Our consultants bring deep expertise in Data Science, Machine Learning and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner. We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.

We are seeking a Senior Data Scientist – Forecasting to join our advanced analytics team supporting leading Retail, CPG, and Supply Chain clients. In this role, you will design, develop, and deploy forecasting solutions that drive critical business decisions across demand planning, inventory optimization, replenishment, logistics, sales forecasting, and supply chain operations.

You will work closely with business stakeholders, data engineers, supply chain planners, and analytics leaders to build scalable forecasting models that deliver measurable business impact. The ideal candidate combines strong statistical forecasting expertise with hands‑on machine learning experience and the ability to translate complex analytical findings into actionable business recommendations.

Key Responsibilities
  • Design, develop, and deploy time-series forecasting models including ARIMA, SARIMA, and ETS
  • Build machine-learning-based forecasting models using GBM, Random Forest, XGBoost, and LightGBM
  • Develop hierarchical and multi-level forecasting solutions across products, regions, and channels
  • Perform large-scale data extraction, transformation, and analysis using SQL
  • Partner with supply chain, merchandising, planning, and business teams to understand forecasting requirements.
  • Translate business problems into analytical solutions.
  • Present model insights and recommendations to senior client stakeholders.
  • Lead workshops and forecasting strategy discussions with clients.
  • Implement and operationalize models in cloud environments
  • Collaborate with business stakeholders to translate demand planning requirements into scalable analytics solutions
Qualifications
  • 10+ years of experience in applied data science or advanced analytics
  • 5+ years of hands‑on experience in demand planning, demand forecasting, or sales forecasting
  • Strong domain experience in CPG, FMCG, retail, or similar industries
  • Advanced proficiency in Python (pandas, NumPy, scikit-learn, statsmodels)
  • Strong SQL skills for large-scale data processing
  • Proven experience deploying models in cloud environments (Azure preferred)

This position offers an excellent opportunity for significant career development in a fast-growing and challenging entrepreneurial environment with a high degree of individual responsibility.

Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status or any other basis as protected by federal, state or local law.

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