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Data Scientist Forecasting Weekend 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

$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 ...

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.

Analytica

Data Scientist

Bethesda, MD · On-site

Mentor junior analysts and data scientists in best practices for data science, forecasting, and ... statistical modeling. Requirements * Bachelor's degree in Data Science, Statistics, Applied ...

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Data Scientist Forecasting Weekend information

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$122.7K

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

As of Sep 11, 2026, the average yearly pay for data scientist forecasting weekend in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is a data scientist forecasting weekend?

Data Scientist Forecasting Weekend roles involve using statistical methods and machine learning techniques to predict trends, demands, or behaviors specifically for weekend periods. These professionals analyze large datasets to identify patterns that occur on weekends, such as sales fluctuations, customer activity, or resource needs. Their insights help businesses optimize staffing, inventory, and operations for better efficiency and profitability during weekends. Typically, they work with tools like Python, R, SQL, and specialized forecasting software. The role may require working weekends or providing analyses that inform weekend business strategies.

What are some common challenges data scientists specializing in forecasting face when working weekend shifts?

Data Scientists focused on forecasting during weekend shifts often encounter unique challenges such as limited access to key stakeholders for immediate clarifications, handling real-time data anomalies without full team support, and ensuring that time-sensitive predictions are delivered accurately under tight deadlines. Additionally, maintaining effective communication with cross-functional teams who may not be working at the same time can require proactive planning and thorough documentation. However, weekend shifts may also offer quieter work periods for deep analysis and model refinement, allowing for focused progress on complex forecasting tasks.

What are the key skills and qualifications needed to thrive as a data scientist specializing in forecasting on weekends, and why are they important?

To thrive as a Data Scientist in Forecasting, you need expertise in statistical modeling, time series analysis, and a strong background in mathematics or computer science, often supported by a relevant degree. Familiarity with programming languages like Python or R, experience with machine learning libraries (such as scikit-learn or TensorFlow), and proficiency in data visualization tools are crucial. Analytical thinking, problem-solving, and effective communication are important soft skills to interpret data and present actionable insights to stakeholders. These skills ensure accurate predictions, drive data-driven decisions, and support organizational goals in dynamic business environments.

What is the difference between Data Scientist Forecasting Weekend vs Data Analyst Forecasting Weekend?

AspectData Scientist Forecasting WeekendData Analyst Forecasting Weekend
Required CredentialsBachelor's or Master's in Data Science, Statistics, or related field; often some experience with machine learningBachelor's in Data Analysis, Statistics, or related field; focus on data interpretation and reporting
Work EnvironmentCollaborative teams, often in tech or finance industries, working on predictive modelsBusiness units, focusing on data reporting, visualization, and basic analysis
Employer & Industry UsageTech companies, finance, e-commerce, and consulting firmsRetail, marketing, healthcare, and finance sectors

Data Scientist Forecasting Weekend roles typically require advanced statistical and machine learning skills, working on predictive models. Data Analyst Forecasting Weekend positions focus on data interpretation, reporting, and visualization. Both roles involve forecasting but differ in complexity and technical depth.

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Data Scientist Forecasting Weekend 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

Other

Re-posted 6 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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