Senior Data Scientist

campbellsoup; New Jersey; On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Medical benefits

Dental benefits

401(k) with immediate vesting

Paid time off

On-site fitness center (WHQ)

Volunteer donation matching

ERGs

Job summary

Campbell Soup Company is seeking a Senior Data Scientist to lead the development and deployment of advanced analytics, ML, and AI solutions that drive measurable business value. You will partner with stakeholders across the organization to transform complex challenges into scalable analytics products and influence strategic decisions.

You will own end-to-end model lifecycle, collaborate with data engineering, and mentor junior data scientists while advancing analytics standards and governance.

Qualifications

• Master's degree in a quantitative field or equivalent practical experience.
• 4+ years in production analytics and ML deployment.
• Strong foundation in probability, statistics, ML, forecasting, experimentation, causal inference, optimization.
• Proficiency in Python and/or R; experience building scalable, tested analytics solutions.
• 2+ years SQL and modern data platforms.

Responsibilities

• Lead end-to-end analytics solutions including ML, AI, optimization, and data mining.
• Source, clean, engineer, and validate data for reproducible models.
• Deploy, monitor, and maintain production models with CI/CD and drift detection.
• Partner with Supply Chain, Finance, Marketing, Sales, and R&D to drive ROI.
• Design experiments including A/B testing to evaluate business initiatives.
• Create visualizations and narratives for senior leadership.
• Collaborate with data engineering to improve platforms and evaluate new tech.
• Mentor junior data scientists and promote best practices.
• Contribute to analytics standards and training programs.

Skills

Machine Learning

Python

R

SQL

Statistical Modeling

Experimentation

Education

Master's degree in Statistics, Computer Science, Mathematics, Engineering, OR related field

Equivalent practical experience

Tools

CI/CD pipelines

Version control

Job description

Since 1869, we've connected people through food they love. We're proud to be stewards of amazing brands that people trust. Our portfolio includes the iconic Campbell's brand, as well as Cape Cod, Chunky, Goldfish, Kettle Brand, Lance, Late July, Pacific Foods, Pepperidge Farm, Prego, Pace, Rao's Homemade, Snack Factory, Snyder's of Hanover. Swanson, and V8.

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.

HOW YOU WILL MAKE HISTORY HERE...

As a Senior Data Scientist, you will serve as a hands-on technical leader responsible for scoping, developing, and operationalizing advanced statistical, machine learning, and AI solutions that deliver measurable business value for Campbell's. You will partner with business and technical leaders across the organization to transform complex, ambiguous challenges into scalable, production-ready analytics products. Through your expertise, leadership, and mentorship, you will elevate data science capabilities, influence strategic decision-making, and help position Campbell's as a data-driven market leader and preferred retail partner.

WHAT YOU WILL DO...

• Lead the end-to-end development of advanced analytics solutions, including Machine Learning, Deep Learning, Artificial Intelligence, Optimization, Simulation, Data Mining, and Multivariate Statistical techniques such as clustering, regression, PCA, hypothesis testing, and factor analysis.
• Translate complex and unstructured data into actionable insights by sourcing, cleansing, engineering, and validating data while ensuring reproducibility, quality assurance, and model governance.
• Own the deployment, monitoring, and lifecycle management of production models in partnership with Data Engineering and ML Engineering teams, including CI/CD, drift detection, model retraining, and performance monitoring.
• Partner with stakeholders across Supply Chain, Finance, Marketing, Sales, and R&D to identify high-impact opportunities and develop data science solutions that generate measurable business outcomes and ROI.
• Design and lead experimentation strategies, including A/B testing and quasi-experimental approaches, to evaluate business initiatives and support data-driven decision-making.
• Develop compelling visualizations, presentations, and business narratives that translate technical findings into actionable recommendations for senior leadership and non-technical audiences.
• Collaborate with data engineering teams to enhance data and machine learning platforms, evaluate emerging technologies, and recommend improvements that increase scalability, speed, and reliability.
• Mentor and coach junior data scientists through code reviews, methodology guidance, technical leadership, and best practices.
• Contribute to the development of analytics standards, reusable assets, technical documentation, recruiting efforts, training programs, and data science communities of practice across the organization.

WHO YOU WILL WORK WITH...

• Data Science, Data Engineering, and ML Engineering teams
• Supply Chain, Finance, Marketing, Sales, and R&D leaders
• Business stakeholders and decision-makers across Campbell's
• Internal analytics communities and cross-functional project teams
• Senior leadership teams responsible for strategic business initiatives
• External retail partners as part of joint value creation opportunities

WHAT YOU BRING TO THE TABLE... (MUST HAVE)

• Master's degree in Statistics, Computer Science, Mathematics, Engineering, Operations Research, or a related quantitative field; equivalent practical experience will also be considered.
• 4+ years of hands-on experience developing and deploying advanced analytics, machine learning, and statistical models in production environments.
• Strong foundation in data science methodologies, including probability, statistics, supervised and unsupervised learning, forecasting, experimentation, causal inference, and optimization.
• Advanced proficiency in Python and/or R with experience building scalable, modular, tested, and version-controlled analytical solutions.
• 2+ years of experience working with SQL and modern data platforms such