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Data Scientist Cpg Jobs in Florida (NOW HIRING)

SAP Director

Miami, FL · On-site

$180 - $240/hr

Life Science, CPG, High Tech Manufacturing * Documented SAP S/4HANA (FICO, MM/IM, SD, PP, QM, SM ... Provides business process input to technical consultants addressing data migration, integration and ...

Life Science, CPG, High Tech Manufacturing * Documented SAP S/4HANA (FICO, MM/IM, SD, PP, QM, SM ... Provides business process input to technical consultants addressing data migration, integration and ...

Life Science, CPG, High Tech Manufacturing * Documented SAP S/4HANA (FICO, MM/IM, SD, PP, QM, SM ... Provides business process input to technical consultants addressing data migration, integration and ...

Data Architect

Plantation, FL · On-site

$60.75 - $78/hr

Bachelor's degree in computer science, computer information systems, or a related field is a plus ... Experience in the CPG industry is a plus This is not designed to cover or contain a comprehensive ...

Data Architect

Plantation, FL · On-site

$120 - $180/hr

Bachelor's degree in computer science, computer information systems, or a related field is a plus ... Experience in the CPG industry is a plus This is not designed to cover or contain a comprehensive ...

Data Architect

Plantation, FL · On-site

$60.75 - $78/hr

Bachelor's degree in computer science, computer information systems, or a related field is a plus ... Experience in the CPG industry is a plus This is not designed to cover or contain a comprehensive ...

Automation Engineer

Clearwater, FL · On-site

$100K - $160K/yr

Computer Science, Computer Engineering, Data Science, AI/ML EXPERIENCE : * Proficiency in at least one backend language: e.g. Python, TypeScript/Node.js, or C#/.NET * Ability to build automation ...

Packaging Engineer

Boca Raton, FL · On-site

$70 - $90/hr

Develop and maintain packaging specifications and master data within SAP * Partner with suppliers ... Science, or related field * 3-5+ years of experience in packaging development; experience in CPG or ...

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Data Scientist Cpg information

What is a data scientist CPG?

Data Scientist CPG roles involve leveraging data analytics, machine learning, and statistical modeling to help Consumer Packaged Goods (CPG) companies make informed business decisions. These professionals analyze large datasets related to consumer behavior, sales, supply chain, and marketing to uncover trends and insights. Their work supports product development, marketing strategies, demand forecasting, and inventory management. Data Scientists in CPG often collaborate with cross-functional teams to drive growth and efficiency across the business.

What are the key skills and qualifications needed to thrive as a data scientist in the Consumer Packaged Goods (CPG) industry?

To thrive as a Data Scientist in CPG, you need strong analytical skills, expertise in statistics, and proficiency in programming languages like Python or R, often supported by a degree in data science, statistics, or a related field. Familiarity with data visualization tools (e.g., Tableau), machine learning frameworks, and experience with large-scale data systems are typically required. Strong business acumen, problem-solving abilities, and effective communication skills help translate data insights into actionable business strategies. These skills are vital for driving data-driven decisions that optimize supply chains, marketing, and product development in the highly competitive CPG sector.

How do data scientists in the CPG industry typically collaborate with marketing and sales teams to drive business outcomes?

Data Scientists working in the Consumer Packaged Goods (CPG) sector regularly partner with marketing and sales teams to analyze consumer behavior, forecast demand, and optimize promotional strategies. They translate complex data into actionable insights, enabling teams to make data-driven decisions on product launches, pricing, and campaign effectiveness. This collaboration often involves presenting findings in clear, business-friendly terms, and aligning data initiatives with broader commercial objectives to ensure that analytics directly contribute to revenue growth and market share.

What is the difference between Data Scientist Cpg vs Data Analyst Cpg?

AspectData Scientist CpgData Analyst Cpg
Required CredentialsBachelor's/Master's in Data Science, Statistics, or related field; programming skills in Python/RBachelor's in Analytics, Statistics, or related field; proficiency in Excel, SQL
Work EnvironmentAdvanced analytics, predictive modeling, machine learning in CPG companiesData reporting, visualization, and basic analysis in CPG settings
Employer & Industry UsageUsed for complex data modeling, forecasting, and strategic insights in CPGUsed for routine data reporting and trend analysis in CPG

Data Scientist Cpg roles focus on advanced analytics, predictive modeling, and machine learning to drive strategic decisions, requiring higher technical skills. Data Analyst Cpg positions involve data reporting, visualization, and basic analysis, supporting operational needs. Both roles are vital in CPG companies but differ in complexity and technical expertise.

What cities in Florida are hiring for Data Scientist Cpg jobs?

Cities in Florida with the most Data Scientist Cpg job openings:

Infographic showing various Data Scientist Cpg job openings in Florida as of August 2026, with employment types broken down into 95% Full Time, 2% Temporary, and 3% Contract. Highlights an 83% In-person, 4% Hybrid, and 13% Remote job distribution.

$104K - $130K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

This job post has expired today. Applications are no longer accepted.


Job description

Manager Data Scientist – Tampa, FL

At PMI U.S., we are building a modern nicotine business—focused on helping make a future without cigarettes a reality in America. As the U.S. businesses of Philip Morris International, we are investing in new products, science, and capabilities to provide the approximately 25 million legal age adults who still smoke with better alternatives.

Our approach is rooted in innovation, responsible marketing, and a growing U.S. footprint that spans manufacturing, technology, and commercial operations across the country.

That creates real opportunity. You'll have the space to take ownership, develop new ideas, and contribute to work that is shaping our business and the category. We're looking for people who are curious, collaborative, and motivated by progress—because the scale of what we're building creates room to grow in different directions.

About the Role

We are seeking a Manager, Data Science (Advanced Analytics) to design and deliver high-impact predictive and prescriptive analytics solutions that directly inform business decisions.

This role is a hands-on advanced analytics practitioner, not focused on descriptive reporting, dashboard development, or KPI tracking. Instead, it requires deep expertise in statistical modeling, forecasting, machine learning, and analytical problem solving, with a proven ability to translate complex business problems into scalable, decision-ready solutions.

You will operate as a technical owner of analytics use cases, partnering with business, product, and data platform teams to take solutions from problem framing through deployment and ongoing optimization.

While this role may provide guidance or mentorship to junior team members, it is primarily an individual contributor role with accountability for outcomes, not team size.

Your 'Day to Day':

1. Advanced Analytics & Modeling (Core Focus)

  • Design, build, and validate predictive and prescriptive models addressing key business problems (e.g., demand forecasting, pricing elasticity, promotion effectiveness, consumer behavior).
  • Apply appropriate techniques including time-series forecasting, regression, classification, optimization, or simulation based on business need.
  • Select modeling approaches grounded in business context, data constraints, interpretability, and scalability, not theoretical novelty.

2. End-to-End Use Case Ownership

  • Own analytics initiatives from problem framing → data exploration → model development → deployment → performance monitoring.
  • Translate ambiguous business questions into structured analytical problems with clear success criteria.
  • Continuously refine models based on real-world performance and stakeholder feedback.

3. Operationalization & Adoption

  • Partner with data engineering and platform teams to ensure models move beyond proof-of-concept into production or repeatable business workflows.
  • Embed outputs into planning cycles, commercial decision processes, and operational routines.
  • Monitor model performance, identify drift, and recommend enhancements or retirement as needed.

4. Business Communication & Influence

  • Communicate analytical approaches, assumptions, and limitations clearly to non-technical stakeholders.
  • Frame outputs as scenarios, trade-offs, and business implications, not just model results.
  • Act as a trusted analytics partner to business stakeholders.

5. Analytics Craft & Reusability

  • Develop reusable analytical assets, frameworks, and modeling components to reduce one-off effort.
  • Ensure proper documentation, explainability, and auditability of models.
  • Contribute to analytics standards and best practices across the organization.

Key Skills:

  • Bachelor's degree in Statistics, Mathematics, Economics, Data Science, Engineering, or related field (Master's preferred).
  • 5–8+ years of experience in data science or advanced analytics roles with demonstrated hands-on modeling experience.
  • Proven track record of delivering model-driven analytics, not just reporting or dashboards.
  • Strong proficiency in Python and/or R, with practical application of statistical and machine learning methods.
  • Experience with:
    • Forecasting, regression, classification, and/or optimization models
    • Working with large, complex, imperfect datasets (e.g., retail scan, consumer panels, transactional data)
  • Ability to translate analytics into business decisions and measurable outcomes.

Preferred Qualifications:

  • Experience in CPG, Retail, or Commercial Analytics environments.
  • Hands-on work in areas such as:
    • Pricing & promotion effectiveness
    • Demand forecasting
    • Revenue Growth Management (RGM)
    • Consumer behavior analytics
  • Experience with cloud data platforms (e.g., Snowflake, Databricks).
  • Familiarity with deploying and operationalizing models in production environments.
  • Ability to balance accuracy, interpretability, and business usability.

Annual Base Salary Range: $104,000 - $130,000

What We Offer:

  • We offer a competitive base salary, annual bonus (applicable based on level of position), great medical, dental and vision coverage, 401k with a generous company match, incredible wellness benefits, commuter benefits, pet insurance, generous PTO, and much more!
  • We have implemented Smart Work, a hybrid model of working that promotes flexibility in the workplace.
  • Seize the freedom to define your future and ours. We'll empower you to take risks, experiment and explore.
  • Be part of an inclusive, diverse culture where everyone's contribution is respected; collaborate with some of the world's best people and feel like you belong.
  • Pursue your ambitions and develop your skills with a global business – our staggering size and scale provides endless opportunities to progress.
  • Take pride in delivering our promise to society: To improve the lives of millions of smokers.

PMI is an Equal Opportunity Employer.

PMI is headquartered in Stamford, Conn., and its U.S. affiliates have more than 3,000 employees.