Interested in this Data Scientist role at Nestlé Purina?
Apply Now →Skills & Technologies
About This Role
Driven by integrity and united by the people\-and\-pet bond, we find strong purpose in the work we do and an even greater joy in those we get to work alongside. Together, we harness the expertise of our long\-standing tradition of excellence to embrace possibility and continuously push to do what's never been done before in pet care. Discover your purpose and fuel your passions when you bring your love of pets to a team that prides itself on the power of togetherness—We are Proudly Connected. Purely Driven.
Position Summary
Digital Transformation is at the center of all that we do. With data\-driven innovators passionate about making a difference in the lives of pets, we create cutting\-edge digital business models that solve complex problems. You'll be at the forefront of digital advancements as they happen in real time, as well as ensure we remain a leader and innovator in the pet care category. Have a hand in making a lasting impact within our long\-standing history.
As a Data Scientist at Nestlé Purina, you'll build and deploy the machine learning and optimization models that drive real business value across functions such as Manufacturing, Marketing, Supply Chain, Finance, and Consumer Insights. At the core of this role is traditional machine learning and optimization, building the models and optimization engines that power some of our highest\-value business decisions. Working closely with cross\-functional teams, you'll translate business problems into scalable analytical solutions, automate insights, and support enterprise decision\-making.
- Develop and deploy machine learning, statistical, and optimization models that solve business problems and improve operational performance
- Support the development and maintenance of optimization engines that drive high\-value business decisions
- Collaborate with product owners, data engineers, and business stakeholders to translate business needs into scalable analytical solutions
- Perform data wrangling, feature engineering, exploratory data analysis, and model evaluation using Python and SQL
- Design and maintain reusable analytics workflows and automated pipelines for production\-grade deployment
- Support GenAI\-enabled applications including retrieval augmented generation (RAG), copilots, and intelligent assistants
- Contribute to AIOps/MLOps practices including model versioning, monitoring, continuous integration and continuous deployment pipelines, and responsible AI processes
Requirements
- Bachelor's degree from an accredited institution in Data Science, Computer Science, Statistics, Engineering, Mathematics, or a related field
- 3\+ years of professional experience in data science, analytics, or machine learning, including developing optimization or predictive models
- 3\+ years of experience in Python (e.g., scikit\-learn, pandas, PySpark, and NumPy) and SQL for data manipulation and analysis
- 1\+ years of experience working with cloud computing platforms (e.g., Azure, AWS, or GCP) and DevOps/CI\-CD practices
Other
- Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field is preferred
- Experience with MLOps tools (e.g., MLflow, Azure ML, SageMaker, or Kubeflow) and model deployment in a production environment is preferred
- Experience working with Databricks, Snowflake, or distributed data processing environments is preferred
- Experience building GenAI\-enabled applications such as RAG, copilots, or intelligent assistants is preferred
- Familiarity with LLM orchestration frameworks (e.g., LangChain or Semantic Kernel), prompt engineering, and vector databases is preferred
- Familiarity with responsible AI practices including bias detection, explainability, and governance is preferred
Don't meet all the qualifications listed under "Other"? These are preferred, but not required. When you apply for a role with Nestlé, we ensure that individual confidentiality is held to the highest regard. We are intentional about creating an inclusive workplace for everyone. We consider our associates our most valuable assets. Please apply for full consideration.
The approximate pay range for this position is $88,000 to $123,000 per year. Final compensation may vary based on factors including but not limited to knowledge, skills and abilities as well as geographic location. Nestlé offers performance\-based incentives and a competitive total rewards package, which includes a 401k with company match, healthcare coverage and a broad range of other benefits. Learn more at https://nestlejobs.com/nestle\-in\-the\-us.
It is our business imperative to remain a very inclusive workplace.
To our veterans and separated service members, you're at the forefront of our minds as we recruit top talent to join Nestlé. The skills you've gained while serving our country, such as flexibility, agility, and leadership, are much like the skills that will make you successful in this role. In addition, with our commitment to an inclusive work environment, we recognize the exceptional engagement and innovation displayed by individuals with disabilities. Nestlé seeks such skilled and qualified individuals to share our mission where you’ll join a cohort of others who have chosen to call Nestlé home.
The Nestlé Companies are equal employment opportunity employers. All applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status or any other characteristic protected by applicable law. Prior to the next step in the recruiting process, we welcome you to inform us confidentially if you may require any special accommodations in order to participate fully in our recruitment experience. Contact us at accommodations@nestle.com or please dial 711 and provide this number to the operator: 1\-800\-321\-6467\.
This position is not eligible for Visa Sponsorship.
Review our applicant privacy notice before applying at https://www.nestlejobs.com/privacy.
Job Requisition: 409964
Salary Context
This $88K-$123K range is in the lower quartile for Data Scientist roles in our dataset (median: $155K across 226 roles with salary data).
View full Data Scientist salary data →Role Details
About This Role
Data Scientists extract insights and build predictive models from data. In the AI era, many roles now include LLM-powered analytics, automated reporting, and integration with generative AI tools. The role has evolved from 'the person who runs SQL queries' to 'the person who builds AI-powered data products.'
Modern data science roles fall into two camps: analytics-focused (insights, dashboards, experimentation) and ML-focused (building predictive models, recommendation systems, NLP features). The best data scientists can operate in both modes. The AI shift means that even analytics-focused roles now involve building automated insight pipelines using LLMs, going well beyond one-off reports.
Across the 3,708 AI roles we're tracking, Data Scientist positions make up 8% of the market. At Nestlé Purina, this role fits into their broader AI and engineering organization.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
What the Work Looks Like
A typical week includes: analyzing experiment results for a product feature launch, building a predictive model for customer churn, creating an automated reporting pipeline using LLM-powered summarization, presenting insights to stakeholders, and cleaning data (always cleaning data). The ratio of analysis to engineering varies by company, but expect both.
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
Skills Required
Python, SQL, and statistical modeling are the foundation. Increasingly, roles want experience with LLMs for data analysis, automated insight generation, and building AI-powered data products. Familiarity with cloud data platforms (Snowflake, BigQuery, Databricks) and ML frameworks (scikit-learn, PyTorch) covers most job requirements.
Experimentation design and causal inference are underrated skills that separate strong candidates. Companies care about whether their product changes cause improvements, and can distinguish causation from correlation. A/B testing methodology, Bayesian statistics, and the ability to communicate uncertainty to non-technical stakeholders are high-value skills.
Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
Compensation Benchmarks
Data Scientist roles pay a median of $192,890 based on 463 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($105K) sits 45% below the category median. Disclosed range: $88K to $123K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Nestlé Purina AI Hiring
Nestlé Purina has 1 open AI role right now. They're hiring across Data Scientist. Based in St. Louis, MO, US. Compensation range: $123K - $123K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 median).
Career Path
Common paths into Data Scientist roles include Data Analyst, Statistician, Quantitative Researcher.
From here, career progression typically leads toward Senior Data Scientist, ML Engineer, AI Product Manager.
Start with statistics and SQL. Build a real analysis project on public data that demonstrates insight generation alongside model building. The market values data scientists who can communicate findings clearly to business stakeholders. If you want to move toward ML engineering, invest in software engineering fundamentals and production deployment skills.
What to Expect in Interviews
Interviews combine statistics, coding, and business acumen. SQL is almost always tested, often with complex joins and window functions. Expect a case study round where you're given a business problem and asked to design an analysis plan. Coding rounds focus on pandas, statistical modeling, and visualization. The strongest differentiator is how well you communicate insights to non-technical stakeholders during presentation rounds.
When evaluating opportunities: Good postings specify the data stack, the types of problems you'll work on, and the team structure. Look for companies that differentiate between analytics and ML data science. Vague 'data scientist' postings that list every skill under the sun usually mean the company doesn't know what they need.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
Data Scientist roles remain in high demand, though the definition keeps shifting. Companies increasingly want candidates who can bridge traditional statistics with modern ML and LLM capabilities. The 'pure insights' data scientist role is consolidating into analytics engineering, while the 'build models' data scientist role is merging with ML engineering.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.