Lead Data Scientist

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. 

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.

How you will make history here...

The Lead Data Scientist is a strategic technical leader who sets the direction, standards, and roadmap for advanced analytics and machine learning at Campbell's. This role owns a portfolio of high-impact initiatives. It is accountable for selecting the highest-value problems, architecting scalable AI/ML solutions, and ensuring adoption and measurable financial impact. The Lead Data Scientist serves as a trusted advisor to senior business leaders, leads and develops a team of data scientists, and partners with engineering and platform teams to institutionalize best practices. The ideal candidate combines deep quantitative expertise and modern engineering judgment with CPG domain fluency and the executive presence to drive transformational outcomes.

What will you be doing...

• Define and drive the data science strategy and multi-year roadmap across priority domains (Supply Chain, Finance, Marketing, Sales, and R&D). Prioritize opportunities by value and feasibility, and translate them into funded, executable programs.

• Architect and lead delivery of complex analytical solutions to drive joint value creation with retail partners and strengthen Campbell's position as a preferred supplier. Methods include Machine/Deep Learning, Generative AI, Multivariate Statistics (e.g., clustering, PCA, regression, hypothesis testing, factor analysis), Causal Inference, Optimization, Data Mining, and Simulation.

• Own value realization for the data science portfolio: build business cases, define success metrics, and track and report realized financial impact to senior leadership.

• Serve as the senior analytics partner to executive stakeholders. Frame ambiguous business challenges, align leadership on priorities and trade-offs, and drive adoption of solutions.

• Act as the technical authority on flagship initiatives. Lead architecture and model reviews, and remain hands-on to prototype novel approaches and unblock difficult problems.

• Set and enforce standards for modeling rigor, code quality, reproducibility, model governance, and responsible AI (including GenAI safeguards) across the data science organization.

• Design and oversee experimentation strategy (A/B testing, quasi-experimental and causal inference methods) to ground decisions in rigorous measurement of impact.

• Lead, coach, and develop a team of data scientists through technical mentorship, career development, and performance feedback. Lead recruiting of senior talent.

• Drive the internal community of practice, represent Campbell's data science externally, and communicate complex concepts through compelling narratives tailored to executive audiences.

Who will you work with

• Partner with Data Engineering, ML Engineering, and Platform teams to shape the enterprise ML platform (MLOps/LLMOps, CI/CD, monitoring, and retraining frameworks). Evaluate emerging technologies and vendors, and make build/buy recommendations.

What you bring to the table...(Must have)

• MS in Statistics, Computer Science, Mathematics, Engineering, Operations Research, or a related quantitative field (PhD strongly preferred). Equivalent practical experience considered.

• Experience: 8+ years of progressive data science experience (6+ with PhD). Must have a track record of leading cross-functional initiatives from ideation through production and measurable business impact, and 2+ years leading or mentoring data scientists.

• Technical depth: Expert-level command of probability and statistics, supervised/unsupervised learning (classification, regression, clustering, GBMs, deep learning), time-series/forecasting, experimentation and causal inference, optimization (formulation and solution), and simulation.

• Generative AI: Working knowledge of LLM-based applications (e.g., RAG, fine-tuning, evaluation) and their appropriate use, limitations, and risks.

• Programming: Expert proficiency in Python and/or R building production-grade analytics (tested, modular, version-controlled code), with the ability to set engineering standards for a team.

• Databases & data processing: Advanced SQL and extensive experience with modern data platforms (e.g., Snowflake, Databricks/Spark), including data modeling and performance tuning at scale.

• Libraries & tools: Deep proficiency with pandas, NumPy/SciPy, scikit-learn, XGBoost/LightGBM, TensorFlow/PyTorch, and statsmodels. Strong experience with optimization libraries (e.g., Gurobi, PuLP) preferred.

• MLOps & engineering practices: Proven experience architecting production ML systems using MLflow, Docker/containers, Git, and CI/CD, including model monitoring, feature stores, and lifecycle management.

• Cloud: Significant experience with Microsoft Azure (Databricks, Synapse, Azure ML, Azure OpenAI, AKS, Functions, storage) or equivalent, with the ability to guide architecture decisions.

• Leadership & influence: Proven ability to tie analytics to P&L outcomes, align senior stakeholders, develop talent, and drive adoption across a large, matrixed organization. Exceptional written and verbal communication, and strong facility with Power BI and/or Tableau.

• Domain: Significant experience in CPG or retail analytics (pricing/promo, demand forecasting, assortment, supply chain optimization, trade spend, marketing mix) strongly preferred.

Compensation and Benefits:

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

$132,100-$181,600

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.