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About This Role
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We are the people who give possibilities purpose
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BD is one of the largest global medical technology companies in the world. Advancing the world of health™ is our Purpose, and it’s no small feat. It takes the imagination and passion of all of us—from design and engineering to the manufacturing and marketing of our billions of MedTech products per year—to look at the impossible and find transformative solutions that turn dreams into possibilities.
Job Description
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Summary:
The Senior Manager of People Analytics, Insights \& AI will serve as the strategic and technical leader responsible for advancing how BD uses people data to drive workforce decisions and business performance. This is a senior people\-manager role combining deep analytical expertise with a strong emphasis on change leadership, business partnership, and practical adoption of analytics across the enterprise. The position will be reporting to the Director of “People Analytics and Insights”.
The right candidate brings not just the ability to build sophisticated models and dashboards, but the business judgment to know what questions matter most, the communication skills to make findings land with senior leaders, and the persistence to drive meaningful change in how people data is used day to day.
Responsibilities:
*Strategic Business Partnership \& Advisory*
- Partner with senior HR and business leaders to frame complex workforce challenges as analytical problems with clear, data\-driven answers connected to business outcomes.
- Serve as a trusted advisor to HR Business Partners, equipping them with workforce insights and decision support tools that strengthen their strategic impact.
- Translate analytical findings into compelling narratives that anchor the “so what” in business terms for non\-technical audiences, including VPs and Senior Directors.
- Proactively identify where people’s analytics can add measurable value and develop structured cases that articulate the problem, solution, and expected impact.
*Advanced Analytics \& Insight Development*
- Lead the design and delivery of advanced analytics solutions including predictive modeling, workforce segmentation, attrition risk, talent pipeline assessment, and organizational effectiveness indicators.
- Apply statistical techniques – regression, machine learning, clustering, hypothesis testing – to translate ambiguous business questions into reliable, actionable insights.
- Deliver operational talent reports and KPI scorecards with data\-driven narratives that are clear, interpretable, and decision\-ready for leadership audiences.
- Collaborate with data engineering and IT partners to integrate HR data from multiple sources and build scalable analytics solutions within BD’s data environment.
- Maintain rigorous standards for data quality, integrity, governance, and documentation across all key HR datasets.
*Adoption, Change Leadership \& Business Case Development*
- Own the adoption of people analytics tools and insights across HR and the business – ensuring solutions are understood, trusted, and actively used in decision\-making, not just delivered.
- Design and execute change management plans for analytics initiatives, including stakeholder engagement, training, and feedback loops that build confidence and sustain usage.
- Develop well\-reasoned business cases for analytics investments, clearly articulating the problem, approach, expected ROI, and success criteria.
- Establish a framework for measuring and communicating the value of people analytics, helping leadership understand what the team delivers and why it matters.
- Embed analytics into existing HR and business workflows, identifying and removing barriers to adoption – whether technical, behavioral, or organizational.
*Analytics Visualization \& Storytelling*
- Create executive\-ready dashboards, reports, and presentations in Power BI that educate, inform, and influence decisions across HR and business leadership.
- Set a high standard for data storytelling across the team – ensuring outputs are clear, interpretable, and tailored to the audience.
- Build self\-service reporting capabilities that increase data accessibility and reduce manual reporting burden across the HR function.
*Emerging Technology \& AI Awareness*
- Maintain a working understanding of how AI and generative tools are evolving in the people analytics space, bringing informed perspectives on where BD could responsibly explore these capabilities.
- Partner with Technology and Digital teams to evaluate new tools and platforms, applying sound judgment on accuracy, data privacy, and business relevance.
- Identify opportunities to automate processes and expand team capabilities through practical application of emerging analytics technologies.
*Team Leadership \& Capability Building*
- Lead, coach, and develop a team of people analytics professionals, raising the bar on analytical rigor, visualization quality, and effective business communication.
- Drive prioritization and workload management across the team, maintaining a sustainable pace across strategic and operational commitments.
- Build data literacy and analytics capability across the broader HR function through training, knowledge sharing, and stakeholder engagement.
- Champion a culture of continuous improvement – encouraging the team to challenge the status quo, automate manual work, and consistently raise the quality of analytics at BD.
Minimum Required:
- Bachelor’s degree in Engineering, Computer Science, Mathematics, Statistics, I/O Psychology, HR Management, or Business Analytics, or a related discipline.
- 8\+ years of progressive experience combining HR knowledge, business partnership, and hands\-on analytics.
- 5\+ years of people or workforce analytics experience with large, complex datasets (may run concurrently with HR experience below)
- 5\+ years of applied HR experience across talent acquisition, performance management, compensation, or organizational effectiveness (may overlap with analytics experience above)
- Demonstrated experience leading or influencing analytics teams, through direct management or senior individual contributor team leadership
- Proven track record of driving adoption of analytics tools or insights – including change management, stakeholder engagement, and sustained behavior change.
- Experience developing business cases and articulating ROI for analytics solutions in terms that resonate with senior HR and business leaders.
- Advanced proficiency in Power BI – dashboard development, DAX, data modeling, and administration.
- Experience with predictive modeling, regression, clustering, classification, and applied statistics.
- Experience with Workday reporting or equivalent enterprise HR systems.
Preferred Skills/Knowledge:
- Master’s degree in HR, STEM, Business/People Analytics.
- Strong SQL foundation and data engineering principles; Python experience for analysis or modeling.
- Familiarity with Visier as a people analytics platform.
- Familiarity with Databricks or similar cloud data lakehouse platforms.
Pay Transparency Statement:
At BD, we are committed to supporting our associates’ well\-being, development, and success through a performance\-based culture. For this position, BD offers a competitive compensation package along with the following benefits specific to this role:
- Annual Bonus
- Potential Discretionary LTI Bonus
Health and Well\-being Benefits
- Medical coverage
- Health Savings Accounts
- Flexible Spending Accounts
- Dental coverage
- Vision coverage
- Hospital Care Insurance
- Critical Illness Insurance
- Accidental Injury Insurance
- Life and AD\&D insurance
- Short\-term disability coverage
- Long\-term disability insurance
- Long\-term care with life insurance
Other Well\-being Resources
- Anxiety management program
- Wellness incentives
- Sleep improvement program
- Diabetes management program
- Virtual physical therapy
- Emotional/mental health support programs
- Weight management programs
- Gastrointestinal health program
- Substance use management program
- Musculoskeletal surgery, cancer treatment, and bariatric surgery benefit
Retirement and Financial Well\-being
- BD 401(k) Plan
- BD Deferred Compensation and Restoration Plan
- 529 College Savings Plan
- Financial counseling
- Baxter Credit Union (BCU)
- Daily Pay
- College financial aid and application guidance
Life Balance Programs
- Paid time off (PTO), including all required State leaves
- Educational assistance/tuition reimbursement
- MetLife Legal Plan
- Group auto and home insurance
- Pet insurance
- Commuter benefits
- Discounts on products and services
- Academic Achievement Scholarship
- Service Recognition Awards
- Employer matching donation
- Workplace accommodations
Other Life Balance Programs
- Adoption assistance
- Backup day care and eldercare
- Support for neurodivergent adults, children, and caregivers
- Caregiving assistance for elderly and special needs individuals
- Employee Assistance Program (EAP)
- Paid Parental Leave
- Support for fertility, birthing, postpartum, and age\-related hormonal changes
Leave Programs
- Bereavement leaves
- Military leave
- Personal leave
- Family and Medical Leave (FML)
- Jury and Witness Duty Leave
At BD, we prioritize on\-site collaboration because we believe it fosters creativity, innovation, and effective problem\-solving, which are essential in the fast\-paced healthcare industry. For most roles, we require a minimum of 4 days of in\-office presence per week to maintain our culture of excellence and ensure smooth operations, while also recognizing the importance of flexibility and work\-life balance. Remote or field\-based positions will have different workplace arrangements which will be indicated in the job posting.
Why Join Us?
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To find purpose in the possibilities, we need people who can see the bigger picture, who understand the human story that underpins everything we do. We welcome people with the imagination and drive to help us reinvent the future of healthcare. At BD, you’ll discover a culture in which you can learn, grow and thrive.
We believe that when people connect in person, we learn faster, collaborate more deeply, and build a stronger culture. Join us and enjoy a culture where face\-to\-face collaboration supports your learning, your progress, and your success.
To learn more about BD visit https://bd.com/careers.
Becton, Dickinson, and Company is an Equal Opportunity Employer. We evaluate applicants without regard to race, color, religion, age, sex, creed, national origin, ancestry, citizenship status, marital or domestic or civil union status, familial status, affectional or sexual orientation, gender identity or expression, genetics, disability, military eligibility or veteran status, and other legally protected characteristics.
Required Skills
Optional Skills
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Primary Work Location
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USA NJ \- Franklin LakesAdditional Locations
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Work Shift
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At BD, we reward, support and develop our associates through our comprehensive Total Rewards program. We are committed to attracting and retaining high quality talent by providing reward and recognition opportunities that promote a performance\-based culture, as well as a competitive package of compensation and benefits programs. You can learn more on our career site under "Our Commitment to You."
Our salary or hourly rate ranges reward associates fairly and competitively. We regularly review these ranges and factors, such as location, contribute to the range displayed.
Our pay is based on the role and the necessary skills and education to perform it successfully. The salary or hourly rate offered is determined by the role's specific requirements, including any applicable step rate pay system at the work location. Salary or hourly pay ranges are influenced by labor laws and Collective Bargaining Agreement (CBA) requirements applicable to the work location which may also affect the workplace arrangement of the role.
Salary Range Information
$154,100\.00 \- $246,600\.00 USD Annual
Salary Context
This $154K-$246K range is above the median for AI/ML Engineer roles in our dataset (median: $180K across 1841 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At BD, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $218,750 based on 3,817 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($200K) sits 8% below the category median. Disclosed range: $154K to $246K.
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.
BD AI Hiring
BD has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Franklin Lakes, NJ, US. Compensation range: $246K - $246K.
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 AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
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).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
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
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