Data Scientist

Here, you will make a difference every day. You will be supported to build a rewarding career with opportunities to grow, innovate and inspire. Make history with us.

Why Campbell’s…

• Benefits begin on day one and include medical, dental, short and long-term disability, AD&D, and life insurance (for individual, families, and domestic partners).
• Employees are eligible for our matching 401(k) plan and can enroll on the first day of employment with immediate vesting.
• Campbell’s offers unlimited sick time along with paid time off and holiday pay.
• If in WHQ – free access to the fitness center. Access to on-site day care (operated by Bright Horizons) and company store.
• Giving back to the communities where our employees work and live is very important to Campbell’s. Our “Campbell’s Cares” program matches employee donations and/or volunteer activity up to $1,500 annually.
• Campbell’s has a variety of Employee Resource Groups (ERGs) to support employees.

The Data Science Analyst plays a critical role in supporting the Demand Planning function by developing and enhancing advanced forecasting models. In this role, you will select optimal modeling approaches for different scenarios, tune parameters to improve performance, and supplement models with custom algorithm development when necessary. You will leverage machine learning and advanced analytics to improve forecast accuracy, optimize financial and supply chain performance, and deliver measurable business impact.

What You Will Do…

Model Development

• Develop and refine AI and machine learning models for demand forecasting using techniques such as time series analysis, regression, and ensemble learning

• Conduct exploratory data analysis (EDA) to identify patterns, anomalies, and key demand drivers

• Translate data into actionable insights to understand the impact of promotions, pricing, and external factors on demand

• Use the o9 platform and open-source IDEs for model development, deployment, data management, and visualization

• Monitor and improve forecasting model accuracy, adapting to changing market conditions

• Partner with demand planners, analysts, and business stakeholders to ensure models and insights are practical and impactful

• Demand Planning teams
• Business analysts and data analysts
• Cross-functional business stakeholders
• Supply chain and commercial teams

• 4+ years of experience in data science, forecasting, or advanced analytics (supply chain experience strongly preferred)
• Bachelor’s degree in Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related field
• Strong proficiency in Python, R, SQL, GitHub, and IDEs such as PyCharm or VS Code
• Solid understanding of statistical modeling and machine learning techniques (e.g., time series, regression, ensemble learning)
• Expertise in exploratory data analysis (EDA), data cleaning, and feature engineering
• Strong analytical and problem-solving skills
• Ability to translate complex analyses into clear business insights
• Experience identifying and prioritizing risks
• Continuous improvement mindset

• Master’s degree in a related field
• Forecasting experience
• Experience working with supply chain or demand planning datasets
• Experience with the o9 platform

• Hybrid work model based in Camden, NJ (Monday & Friday remote; Tuesday–Thursday in-office)
• 10–15% travel for company and customer meetings

The target base salary range for this full-time, salaried position is between

$109,400-$157,200

Individual base pay depends on work location and additional factors such as experience, job-related skills, and relevant education or training. Total pay may include other forms of compensation. In addition, we offer competitive health, dental, 401k and wellness benefits beginning on the first day of employment. Please ask your Talent Acquisition Partner for more information about our total rewards package.

The Company is committed to providing equal opportunity for employees and qualified applicants in all aspects of the employment relationship, including consideration for employment, without regard to race, color, sex, sexual orientation, gender identity, national origin, citizenship, marital status, protected veteran status, disability, age, religion, or any other classification protected by law.