Mgr Data Science

We need to output HTML fragment with sections: About the role? Actually the posting includes sections: Why Hershey, About The Hershey Company, How will you fit in the big picture?, What will you do?, Minimum Education & Requirements, Preferred Qualifications, Benefits And Perks, Pay (salary range). We need to use

for section headings (e.g., About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). We must not repeat job title as heading. We must not include Job ID etc. We must include only sections with real specific content. We must not create sections with filler like "commensurate with experience". We have salary range, so Pay section is appropriate. Benefits section: we have benefits description. Schedule: not mentioned, so omit. Skills: maybe we can include under Requirements or Qualifications. The instruction: Use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we can choose appropriate headings based on content. We need to preserve all substantive information, not invent or summarize away detail. Must not repeat job title as heading. Must not put Job ID/requisition numbers as headings. Must remove boilerplate: cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, application instructions. So we need to strip out the EEO statement, accommodation request, etc. Also remove duplicated lines (like repeated "The Hershey Company is an Equal Opportunity Employer"). We need to keep the substantive content: Why Hershey paragraph, About The Hershey Company paragraph(s), How will you fit in the big picture? (role description), What will you do? (list of duties), Minimum Education & Requirements (list), Preferred Qualifications (list), Benefits And Perks (list), Pay (salary range). Also maybe include "About The Hershey Company" as a section heading? Could be "About the company" but not in list. The allowed headings list includes About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We could map: - About the role: could combine Why Hershey and About The Hershey Company? But "About the role" is more about the role itself. However we have "How will you fit in the big picture?" which is about role. Could use "About the role" heading for that. - Responsibilities: for "What will you do?" list. - Requirements: for Minimum Education & Requirements. - Qualifications: for Preferred Qualifications. - Skills: maybe not needed; we could omit if no specific skills section separate. Could embed skills within Requirements/Qualifications. - Benefits: for Benefits And Perks. - Pay: for salary range. - Schedule: omitted. We must not create sections with filler. So we will output sections only for those we have content. We need to use

• for any list of duties/requirements/benefits. For prose, use

  . We must preserve all substantive information; do not invent or summarize away detail. So we need to keep the exact wording? Probably we can keep the substance but not necessarily verbatim; but better to keep close. We must not include boilerplate like EEO, accommodation request, etc. We must not include duplicated lines. Let's extract content: Why Hershey: paragraph about culture, purpose, Milton Hershey, philanthropy, partnership with Milton Hershey School, strategic grantmaking, product donations, cross brand collaboration, employee volunteerism, making a difference. About The Hershey Company: paragraph about company, NYSE: HSY, industry-leading snacks company, iconic brands, list of brands, commitment to making a difference, founder Milton Hershey, employee value proposition Lead Today. Create Tomorrow, One Hershey mindset, top employer recognition. How will you fit in the big picture? paragraph: As a Data Science Manager, you will lead a team of data scientists focused on solving complex business challenges through machine learning, optimization, forecasting, experimentation, and advanced analytics. Partner with engineering, product, and business leaders to identify opportunities where data science can create meaningful business value and help shape the future of snacking. This role combines scientific leadership with people leadership. You will hire, develop, and coach top talent while creating an environment that fosters innovation, collaboration, operational excellence, and customer-focused problem solving. Success requires strong business acumen, sound scientific judgment, stakeholder management skills, and the ability to drive results in a dynamic environment. What will you do? list: - Lead, coach, develop, and retain a high-performing team of data scientists. - Set scientific direction and team priorities aligned with business objectives. - Partner with cross-functional stakeholders to identify and deliver high-impact data science solutions. - Drive execution of complex initiatives across machine learning, optimization, forecasting, decision science, and advanced analytics. - Review technical approaches, provide guidance on solution design, and promote scientific rigor and model quality. - Establish scalable processes and mechanisms that improve team effectiveness and delivery predictability. - Communicate insights, recommendations, risks, and business impact to senior leadership. - Foster a culture of innovation, continuous learning, and data-driven decision making. Minimum Education & Requirements: - Experience: 5+ years of experience applying data science, machine learning, optimization, statistics, or related quantitative disciplines to solve business problems. - 2+ years of people leadership experience, including coaching, developing, or managing technical professionals. - Demonstrated success leading teams and delivering complex data science initiatives in cross-functional environments. - Strong understanding of machine learning, optimization, experimentation, statistical modeling, and advanced analytics. - Experience communicating technical concepts and business insights to both technical and non-technical stakeholders. - Education: Master's degree in Operations Research, Statistics, Machine Learning, Applied Mathematics, Computer Science, Operations Management, or a related quantitative field. Preferred Qualifications: - PhD in Operations Research, Statistics, Machine Learning, Economics, Computer Science, Applied Mathematics, or a related quantitative field. - Experience translating business strategy into data science roadmaps and scientific workstreams. - Knowledge of cloud platforms such as Azure, AWS, or GCP. - Hands-on experience with Python, SQL, Pandas, PySpark, Scikit-learn, TensorFlow, Keras, or similar technologies. - Experience with optimization modeling and commercial solvers such as Gurobi or Xpress. - Demonstrated ability to influence senior leaders and drive organizational change through data and technology. Benefits And Perks: - At Hershey, we offer competitive pay and a comprehensive total rewards package designed to support your wellbeing, financial security, and life outside of work. - Health & Wellbeing: Medical, dental, and vision coverage, plus wellness programs that support your physical and mental health. - Financial Security: Competitive pay, annual incentive opportunities, and a 401(k) with company match. - Time Off & Flexibility: Paid time off, company holidays, and flexible ways of working where applicable. - Growth & Development: Career development programs, learning opportunities, and internal mobility. - Benefits may vary based on role, location, and eligibility. - The anticipated base salary range for this role is $155,840.00 to $194,800.00 per year. - The actual base salary offered will depend on a variety of job‑related factors, including, but not limited to, experience, skill set, education, and training. - In addition to a market-competitive base salary, our Total Rewards package includes performance‑based incentives and a comprehensive, competitive benefits package designed to support overall physical, mental, and financial well‑being (as applicable). - Learn more about Hershey’s benefits and all the resources Hershey provides to support our employees’ physical, emotional, and financial well‑being by visiting the Hershey Digital Employee Experience at www.askHRbenefits.hersheys.com We need to output HTML fragment only, no markdown fences. We need to use

  for section headings. We'll decide sections: - About the role (could combine Why Hershey and About The Hershey Company? Actually "About the role" is about the role, not company. But we have "How will you fit in the big picture?" which is about role. Maybe we can use "About the role" for that paragraph. Then we need a separate section for "About the company"? Not in allowed headings but we could incorporate into "About the role" or maybe we can omit? The instruction: "Use

  for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." It says e.g., meaning those are examples, not exclusive list. So we can use other headings if appropriate, but better to stick to those. However we need to include company description; maybe we can put it under "About the role" as part of role context? Or we could create a section "About the company" but not in list; but it's not prohibited to use other headings, just they gave examples. Safer to use "About the role" for the role description (How will you fit in the big picture?) and maybe include Why Hershey and About The Hershey Company as part of that? But that would mix company info with role. Could also create a section "About the company" but not in examples; but it's probably okay. However the instruction says "Use

  for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." It doesn't forbid other headings, but to be safe we could use those exact headings where applicable and maybe add a "Company Overview" heading if needed. But we might risk violating instruction if we add extra headings not in examples? The examples are not exhaustive; they say e.g., meaning for example. So it's okay to use other headings. However they also say "Prefer a few substantive sections over many thin ones." So we should combine where possible. We could have sections: - About the role (includes Why Hershey, About The Hershey Company, How will you fit in the big picture?) but that might be too thick. Better: Use "About the role" for the role description (How will you fit in the big picture?). Use "Responsibilities" for the What will you do? list. Use "Requirements" for Minimum Education & Requirements. Use "Qualifications" for Preferred Qualifications. Use "Benefits" for Benefits And Perks. Use "Pay" for salary range. We still need to include Why Hershey and About The Hershey Company somewhere. Could we incorporate them into "About the role" as introductory context? Or we could add a section "About the company" but not in examples; but maybe it's okay. However the instruction says "Use

  for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." It doesn't say we cannot use other headings, but they gave examples. I'd stick to those examples and try to fit company info somewhere else. Perhaps we can put Why Hershey and About The Hershey Company under a

  before the first heading, as introductory prose. That would be acceptable: we can have some prose before any heading. The instruction: "Do NOT repeat the job title as a heading (the page already shows it) and do NOT put Job ID / requisition numbers as headings — fold minor metadata into a short

  or drop it." So we can have introductory paragraphs. Thus we can start with a

  containing Why Hershey and About The Hershey Company combined (or separate

  s). Then

  About the role

  with the paragraph about role fit. Then

  Responsibilities

  with
  list. Then

  Requirements

  with
  list. Then

  Qualifications

  with
  list. Then

  Benefits

  with
  list (including benefits description). Then

  Pay

  with

  containing salary range and related details. We must ensure