Director, Data Science
- UNAVAILABLE, United States
Applications open in a new tab.
Job details
- Apply by
- Experience
- 8–12+ years of progressive data science, machine learning, and/or analytics experience
- Posting language
- English
- Posted
Original job description
Company Overview
Why 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.
Company Benefits
What You'll Get From Us
Benefits
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 myHRservices@novolex.com.
Formerly Pactiv Evergreen
More about this job
Skills
- Leadership
- Machine learning
- Sales
- Supply chain management
- Quality control
- Decision making
- Statistics
- ML
- Regulatory compliance
- Data analysis
- Forecasting
- Data engineering
- Python
- R
- SQL
- TensorFlow
- Scikit-learn
- PyTorch
- Engineering principles
- Collaboration
- Change management
- Program management
- Logistics
- Financial capability
- Prioritization
- Coaching
- Communication skills
- Stakeholder management
- Adaptability
- Computer science
- Agile
- Microsoft Azure
- AWS
- Google Cloud
- Databricks
- Informatica
- Apache Kafka
- Mlflow
- GitHub
- Reporting