Director, Data Science

Posted 2 Days Ago
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Hiring Remotely in United States
Remote
170K-220K Annually
Expert/Leader
Industrial • Manufacturing
The Role
Leads enterprise data science, machine learning, predictive and prescriptive analytics, and generative AI adoption. Builds production-grade models for forecasting, pricing, maintenance, supply chain, and quality use cases. Establishes delivery models, governance, responsible AI practices, and business alignment while managing and developing data science talent. Partners with IT and business leaders to demonstrate ROI, translate technical findings, and deploy scalable AI solutions across manufacturing operations.
Summary Generated by Built In
Company OverviewWhy Choose Us?

Novolex is a leading manufacturer of food, beverage, and specialty packaging that supports multiple industries including foodservice, restaurant delivery and carryout, food processing, grocery and retail, and industrial sectors. Novolex manufacturing and sourcing expertise spans a diverse range of substrates including resin, paper, molded fiber, aluminum and more. We provide customers a broad array of stock and customized solutions with 120 product categories, 250 brands and over 39,000 SKUs.

Our Sustainability Commitment

The Novolex sustainability vision is built upon three pillars: our products, our operations and our people. Each is critically important to our growth and future as a business. These pillars form the foundation of our company-wide commitment to sustainability, helping us achieve our ambitious goals through our wide-ranging initiatives.

Job Description

Scope: The data science leader drives advanced analytics delivery and associated AI adoption across the enterprise, balancing centralized enablement with distributed product delivery. This role bridges technical innovation, methodology and business strategy, ensuring data science investments directly support operational and strategic objectives.  Ideal candidates will be based in Charlotte, NC or Lake Forest, IL.



Core Responsibilities


Strategic & Delivery Leadership:

  • Align data science team structure and associated delivery models with organizational predictive/prescriptive analytics & AI maturity (labs, Centers of Excellence, or platform teams)
  • Drive enterprise-wide predictive/prescriptive analytics & AI adoption by optimizing how data science solutions reach business functions
  • Develop hybrid delivery models balancing centralized data science enablement with federated analytics and business teams leveraging an Agile delivery framework and mindset

Technical Execution:

  • Build and develop the organization's data science and machine learning models that solve enterprise-wide challenges (e.g. integrated business planning, pricing, sales planning, predictive maintenance, supply chain optimization, quality control)
  • Support decision-making through statistical analysis, advanced analytics, and prescriptive analytics approaches
  • Develop, adapt, and test generative AI solutions leveraging predictive/prescriptive analytics aligned with manufacturing use cases
  • Predict and classify outcomes using predictive analytics; create next-best-action models for operational decisions 

Team & Capability Building:

  • Collaborate with IT to orchestrate fusion teams integrating data scientists, data & AI/ML engineers, software engineers, and business domain experts to ensure end-to-end collaboration and accelerated business value 
  • Manage AI lifecycle roles across build, test, deploy, and operate phases; adapt team composition based on project complexity and size
  • Work with IT to build enterprise-wide predictive/prescriptive analytics and AI literacy and partner with IT with upskilling programs to equip teams with evolving capabilities in AI, machine learning, and responsible AI practices.
  • Hire, develop, and retain data science talent aligned with enterprise strategic priorities

Governance & Risk Management:

  • Ensure data science models and AI solutions comply with governance frameworks, data ethics standards, and responsible practices
  • Work with governance managers and risk functions to maintain trust and compliance in deployed models
  • Champion data quality and ethical advanced analytics and AI usage across the organization

Business Alignment:

  • Working with the VP Data & Analytics, interface with business leaders to translate business challenges into data science initiatives
  • Translate technical findings into actionable business insights for non-technical stakeholders
  • Demonstrate ROI and business impact of data science initiatives using relevant metrics

Required Skills & Competencies

Technical Expertise:

  • Advanced proficiency in statistical analysis, machine learning, and advanced analytics techniques (regression, classification, clustering, neural networks) with an emphasis on Demand Planning/Forecasting (e.g. time series, exponential smoothing, intermittent demand models, random forest, gradient boosting, demand sensing, etc.)
  • Hands-on experience developing, validating, and deploying production-grade models
  • Familiarity with data platforms, data engineering fundamentals, and ETL/ELT processes
  • Emerging expertise in AI applications relevant to manufacturing industry
  • Proficiency in Python, R, SQL, and common ML frameworks (TensorFlow, scikit-learn, PyTorch)

Data Science & AI Knowledge:

  • Deep expertise in data science methodologies, model lifecycle management, and AI engineering principles
  • Understanding of AI ethics, model governance, bias mitigation, and responsible AI frameworks
  • Knowledge of manufacturing industry domain problems and solutions (sales planning, pricing, predictive maintenance, demand forecasting, quality prediction, anomaly detection)

Leadership & Collaboration:

  • Proven ability to lead cross-functional teams and orchestrate collaboration across data, software, and business functions
  • Strong change management and influence skills to drive adoption of solutions across the enterprise
  • Facilitation and storytelling abilities to communicate complex technical concepts to executives and business teams
  • Project and program management experience at scale

Business Acumen:

  • Strategic thinking aligned with business objectives and competitive positioning
  • Understanding of sales, commercial and manufacturing operations, marketing, supply chain, logistics, finance, and quality functions
  • Financial acumen to articulate ROI, cost-benefit analysis, and resource prioritization
  • Industry knowledge of manufacturing trends, Industry 4.0, and digital transformation initiatives

Soft Skills:

  • Leadership and mentoring capability to develop emerging data science talent
  • Communication, presentation, and stakeholder management skills
  • Adaptability and continuous learning mindset—comfort with evolving methodologies & technologies and organizational needs
  • Empathy, influence, and authority to navigate cross-functional complexities and build trust

Education & Experience

Minimum Education:

  • University degree in Computer Science, Statistics, Mathematics, Engineering, or related STEM field
  • Advanced degree (Master's in Data Science, Statistics, Computer Science, or MBA) preferred

Professional Experience:

  • 8–12+ years of progressive data science, machine learning, and/or analytics experience
  • 3+ years in a leadership role managing data science initiatives or teams
  • Experience in manufacturing, industrial operations, or similar complex environments strongly preferred
  • Proven experience working within an Agile product management framework
  • Track record of managing data science at scale and deploying production machine learning models
  • Demonstrated success leading cross-functional teams and driving enterprise-wide initiatives

Certifications & Training:

  • Proven experience with cloud platforms (e.g. Azure, AWS, GCP), machine learning, and specialized tools (e.g. MS Fabric, Databricks, Informatica, Kafka, Alation, Syndigo, MLflow, OpenAI, GitHub)
  • Internal training or certifications in company-specific tools and frameworks

Organizational Placement & Reporting

Reporting Line: VP of Data & Analytics

Key Relationships:

  • Cross-functional partnerships with Head of Data Engineering, Chief Information Officer, Head of Quality, VP of Operations, and Chief Financial Officer
  • Collaboration with business unit leaders to embed predictive/prescriptive/AI solutions
  • Governance and compliance partnerships with legal, risk, and ethics functions

Span of Influence: 3-5 direct reports (data scientists)


Compensation:

A reasonable estimate of the current range is $170,000 - 220,000 + bonus + benefits. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by job-related skills, experience, and relevant education or training. At Novolex, it is not typical for an individual to be hired at the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case.

 

The benefits for this role include 401(k) plan with company match, comprehensive medical, dental, and vision insurance, flexible spending and health savings accounts, paid vacation, and sick days, paid parental leave, paid holidays and wellness program.


#LI-TM1

Company BenefitsWhat You'll Get From UsBenefits

With safety as our top priority and a commitment to employee well-being an important focus, we offer comprehensive and competitive benefits that include medical, dental and vision insurance as well as a variety of other well-being resources focused on mental, physical and financial health. Specific benefits and well-being programs may vary depending on where you work.

Community Engagement

At Novolex, giving back to the local communities that support us is important. Our Focused Giving Program prioritizes support for organizations whose missions promote sustainability initiatives or address food and hunger needs. We also encourage facility level support of activities in the communities where our employees live and work.

Training and Development

We offer constant opportunities for advancement. From skills development to advanced education programs, training and development programs and courses are available through MyLearning. Programs include company and industry training curricula, support for formal education through the Tuition Reimbursement Program (Non-Union), and a Learning Management System that supports and enhances employee skills at all levels of the organization.


Novolex is committed to providing equal employment opportunity in all employment practices, including but not limited to selection, hiring, promotion, transfer, and compensation to all qualified applicants and employees without regard to age, race, color, national origin, sex, pregnancy, sexual orientation, gender identity, religion, handicap or disability, genetics, citizenship status, service member or veteran status, or any other category protected by federal, state, or local law. Any individual who, because of his or her disability, needs an accommodation in connection with an aspect of the Company's application process should contact [email protected].


Formerly Pactiv Evergreen

Skills Required

  • University degree in Computer Science, Statistics, Mathematics, Engineering, or a related STEM field
  • 8-12+ years of progressive data science, machine learning, and/or analytics experience
  • 3+ years in a leadership role managing data science initiatives or teams
  • Advanced proficiency in statistical analysis, machine learning, and advanced analytics techniques
  • Expertise in demand planning and forecasting methods
  • Hands-on experience developing, validating, and deploying production-grade models
  • Familiarity with data platforms, data engineering fundamentals, and ETL/ELT processes
  • Proficiency in Python, R, SQL, and common machine learning frameworks
  • Knowledge of AI ethics, model governance, bias mitigation, and responsible AI frameworks
  • Experience leading cross-functional teams across data, software, and business functions
  • Strong change management, communication, storytelling, and stakeholder management skills
  • Project and program management experience at scale
  • Strategic thinking, financial acumen, and ability to articulate ROI and cost-benefit analysis
  • Experience working within an Agile product management framework
  • Track record of managing data science at scale and deploying production machine learning models
  • Demonstrated success driving enterprise-wide initiatives
  • Experience with cloud platforms and specialized data and machine learning tools
  • Advanced degree in Data Science, Statistics, Computer Science, or an MBA
  • Experience in manufacturing, industrial operations, or similar complex environments
  • Internal training or certifications in company-specific tools and frameworks

Novolex Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Novolex and has not been reviewed or approved by Novolex.

  • Healthcare Strength — Health coverage is described as broadly available, including medical, dental, and vision, with many finding the cost manageable. Experiences can vary by location and role, but core coverage and wellness resources are commonly highlighted.
  • Retirement Support — A 401(k) with employer matching is highlighted and is perceived as a meaningful component of the package. This benefit stands out among the more consistently praised elements despite site-to-site variations.
  • Leave & Time Off Breadth — Paid time off, paid breaks, and vacation are commonly offered across many roles. These provisions contribute to an overall benefits picture that is seen as acceptable to good depending on the facility.

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The Company
HQ: Charlotte, NC
23,000 Employees
Year Founded: 2003

What We Do

Novolex is a leading manufacturer of food, beverage, and specialty packaging serving foodservice, restaurant delivery and carryout, food processing, grocery and retail, and industrial customers. Its innovative product portfolio helps businesses operate efficiently, meet evolving customer expectations, and deliver everyday essentials to millions of customers worldwide. The company’s manufacturing network spans North America and Europe and includes two plastic-film recycling centers.

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