Data Science Engineer Jobs in New Jersey
Data Science Engineer jobs in New Jersey are consistently in demand, with strong hiring concentrated in pharma and life sciences, financial services, and telecommunications sectors, and openings at every level from entry-level analyst to senior engineer. The most active hiring metros are Newark, Princeton, and Parsippany, where established employers like Johnson and Johnson, Cognizant, and Verizon maintain large technology and analytics teams. Roles requiring machine learning engineering, MLOps, and large-scale data pipeline development are among the most sought-after specialties in the state right now. Find a role that fits below and apply directly.
Find Data Science Engineer JobsOverview
Showing 5 of 12+ Data Science Engineer jobs









Working with Us
Challenging. Meaningful. Life-changing. Those aren’t words that are usually associated with a job. But working at Bristol Myers Squibb is anything but usual. Here, uniquely interesting work happens every day, in every department. From optimizing a production line to the latest breakthroughs in cell therapy, this is work that transforms the lives of patients, and the careers of those who do it. You’ll get the chance to grow and thrive through opportunities uncommon in scale and scope, alongside high-achieving teams. Take your career farther than you thought possible.
Bristol Myers Squibb recognizes the importance of balance and flexibility in our work environment. We offer a wide variety of competitive benefits, services and programs that provide our employees with the resources to pursue their goals, both at work and in their personal lives. Read more: careers.bms.com/working-with-us .
Position Summary
This is a new position. You will join a cutting-edge Drug Development Data Science and Advanced Analytics (DSAA) team as a senior scientific and technical leader, driving data science strategy and execution to advance the global drug development process. We are looking for a seasoned data scientist with a strong computational, statistical, and biological background and a demonstrated track record of leading analytical strategy, driving methodological innovation, and translating complex, multi-modal data into impactful scientific insights that inform clinical development decisions.
As an Associate Director, you will provide scientific leadership across diverse data types generated in drug development — including clinical trial data, genomics, proteomics, imaging, flow cytometry, and other biomarker modalities — driving both the strategic direction and hands-on execution of data science efforts across early-to-late phase drug development programs. You will define and champion analytical frameworks, methodological standards, and scalable approaches that elevate the quality and impact of data science across the organization, while serving as a key scientific partner to Biostatistics leads, Translational and Clinical Scientists, and senior cross-functional stakeholders. This position may include management of a small team of data scientists. We are looking for a technically excellent, scientifically influential, and strategically minded practitioner.
What You'll Do
Data Science Strategy & Scientific Leadership
- Serve as a senior scientific resource within the DSAA organization, providing strategic direction and methodological guidance on data science approaches across multiple drug development programs
- Lead the design and execution of exploratory and confirmatory analyses (both hypothesis-generating and hypothesis-driven) across diverse and complex data types, from early discovery through late-phase clinical development
- Drive the development and implementation of innovative statistical methods, novel analytical frameworks, and state-of-the-art AI/ML approaches to address key scientific questions in drug development
- Shape the analytical strategy for drug development programs, contributing to decisions around trial design, endpoint selection, biomarker strategy, and evidence generation
- Identify opportunities to leverage emerging data science methodologies and technologies to accelerate drug development and address the complexities of novel data types
- Represent DSAA in cross-functional program team meetings, providing authoritative scientific input and influencing development decisions through rigorous, data-driven analysis
Advanced Analytics & Modeling
- Lead the development and application of novel computational methods for patient segmentation, biomarker discovery, and precision medicine from multimodal clinical and omics datasets in partnership with Translational, Clinical, and Statistical Scientists
- Oversee and execute data science analyses on datasets from BMS clinical trials and real-world data cohorts, spanning genomics, proteomics, imaging, flow cytometry, and other high-dimensional biomarker data types
- Drive the integration, mining, and visualization of diverse, high-dimensional, and disparate datasets across therapeutic areas and development phases, developing novel analytical approaches where existing methods fall short
- Lead the formulation, implementation, testing, and validation of predictive models and scalable automated processes for delivering modeling results across multiple programs
- Apply and advance the use of AI/ML, deep learning, NLP, causal ML, and explainable AI across multiple data modalities and clinical development contexts, maintaining currency with the state of the art
- Lead application of rigorous statistical approaches to clinical trial data, including survival analysis, longitudinal/mixed-effects modeling, causal inference, and principled handling of missing data and censoring
- Contribute to and influence the scientific and statistical strategy of drug development programs, including the development of predictive biomarkers, novel trial designs, and precision medicine approaches
Data Engineering & Reproducibility
- Define and champion standards for scalable, reproducible, and well-documented analytical pipelines and codebases using Python, R, SQL, and cloud platforms
- Establish and enforce data quality frameworks to assess and ensure fitness-for-purpose of diverse data sources across programs
- Promote rigorous model evaluation practices including appropriate cross-validation, calibration assessment, out-of-sample validation, and transparent reporting of model performance
- Drive adoption of scalable, automated analytical processes and best-in-class software engineering practices across the team
Leadership, Mentorship & Cross-Functional Influence
- If applicable, manage and develop a small team of data scientists, building capabilities, fostering scientific rigor and innovation, and ensuring delivery of high-quality outputs within program timelines
- Mentor and provide technical guidance to junior and mid-level data scientists, elevating team-wide methodological and engineering standards through code reviews, collaborative problem-solving, and knowledge sharing
- Partner with lead and protocol statisticians in shaping statistical analysis plans (SAPs) for exploratory data science analyses supporting drug development programs
- Collaborate with and influence cross-functional teams including clinicians, translational medicine scientists, biostatisticians, data engineers, regulatory scientists, and IT/engineering professionals
- Communicate complex analytical strategies and results with clarity and scientific authority to both technical and non-technical audiences, including senior leadership
- Build and maintain strong, high-trust working relationships across the organization, establishing DSAA as a valued scientific partner
Key Requirements
- Ph.D. in a relevant quantitative field (e.g., Computational Biology, Biostatistics, Statistics, Biomedical Engineering, Computer Science, or related field) and 6+ years of academic/industry experience; or Master's Degree in a relevant quantitative field and 8+ years of industry experience
- Demonstrated mastery in data science and statistical analysis with data generated from clinical trials or electronic health records, with a strong track record of delivering impactful results in a pharma R&D context
- Significant experience leading the development and application of statistical and machine learning models on high-dimensional data for time-to-event, longitudinal, and multivariate outcomes
- Proven expertise in the application of AI/ML and proficiency in Python, R, SQL, and cloud platforms (e.g., AWS, Azure, Databricks)
- Deep familiarity with clinical trial design, drug development processes, and the role of biomarkers and data science in regulatory and clinical decision-making
- Demonstrated ability to define and drive analytical strategy across multiple concurrent programs, balancing scientific rigor with practical delivery
- Significant track record of driving statistical and AI/ML innovation, with a perspective on leveraging emerging approaches to expedite drug development and address complexities of novel data types
- Demonstrated ability to lead, mentor, and collaborate with multidisciplinary teams, and to manage multiple concurrent high-priority programs with competing timelines
- Excellent communication, data presentation, and visualization skills; ability to convey complex analytical concepts to diverse audiences including senior leadership
- Capable of establishing and sustaining strong, high-trust working relationships across the organization
Preferred Qualifications
- Experience with genomics, proteomics, imaging, flow cytometry, or immunobiology datasets from clinical trials is highly preferred
- Experience with NLP is highly preferred
- Experience with Survival Analysis and time-to-event modeling is highly preferred
- Experience with causal ML and explainable AI is highly preferred
- Knowledge of molecular biology and understanding of disease pathways is preferred
- Experience with real-world data (RWD/RWE) sources, including EHR, claims, or registry data, and associated analytical and causal inference methods is preferred
- Familiarity with digital health data and wearable/sensor-derived data types is a plus
- Experience with or exposure to novel clinical trial design (e.g., adaptive, platform, or biomarker-enriched trials) is preferred
- Prior experience in a people management or formal scientific leadership role is a plus
- Experience with scalable compute and deployment patterns, including cloud-based platforms and parallelization for large-scale data processing and model training is a plus
If you come across a role that intrigues you but doesn’t perfectly line up with your resume, we encourage you to apply anyway. You could be one step away from work that will transform your life and career.
Compensation Overview:
The starting compensation range(s) for this role are listed above for a full-time employee (FTE) basis. Additional incentive cash and stock opportunities (based on eligibility) may be available. The starting pay rate takes into account characteristics of the job, such as required skills, where the job is performed, the employee’s work schedule, job-related knowledge, and experience. Final, individual compensation will be decided based on demonstrated experience.
Eligibility for specific benefits listed on our careers site may vary based on the job and location. For more on benefits, please visit https://careers.bms.com/life-at-bms/.
Benefit offerings are subject to the terms and conditions of the applicable plans in effect at the time and may require enrollment. Our benefits include:
Health Coverage: Medical, pharmacy, dental, and vision care.
Wellbeing Support: Programs such as BMS Well-Being Account, BMS Living Life Better, and Employee Assistance Programs (EAP).
Financial Well-being and Protection: 401(k) plan, short- and long-term disability, life insurance, accident insurance, supplemental health insurance, business travel protection, personal liability protection, identity theft benefit, legal support, and survivor support.
Work-life benefits include:
Paid Time Off
US Exempt Employees: flexible time off (unlimited, with manager approval, 11 paid national holidays (not applicable to employees in Phoenix, AZ, Puerto Rico or Rayzebio employees)
Phoenix, AZ, Puerto Rico and Rayzebio Exempt, Non-Exempt, Hourly Employees: 160 hours annual paid vacation for new hires with manager approval, 11 national holidays, and 3 optional holidays
Based on eligibility*, additional time off for employees may include unlimited paid sick time, up to 2 paid volunteer days per year, summer hours flexibility, leaves of absence for medical, personal, parental, caregiver, bereavement, and military needs and an annual Global Shutdown between Christmas and New Years Day.
All global employees full and part-time who are actively employed at and paid directly by BMS at the end of the calendar year are eligible to take advantage of the Global Shutdown.
*Eligibility Disclosure: T he summer hours program is for United States (U.S.) office-based employees due to the unique nature of their work. Summer hours are generally not available for field sales and manufacturing operations and may also be limited for the capability centers. Employees in remote-by-design or lab-based roles may be eligible for summer hours, depending on the nature of their work, and should discuss eligibility with their manager. Employees covered under a collective bargaining agreement should consult that document to determine if they are eligible. Contractors, leased workers and other service providers are not eligible to participate in the program.
Uniquely Interesting Work, Life-changing Careers
With a single vision as inspiring as “Transforming patients’ lives through science™ ”, every BMS employee plays an integral role in work that goes far beyond ordinary. Each of us is empowered to apply our individual talents and unique perspectives in a supportive culture, promoting global participation in clinical trials, while our shared values of passion, innovation, urgency, accountability, inclusion and integrity bring out the highest potential of each of our colleagues.
On-site Protocol
BMS has an occupancy structure that determines where an employee is required to conduct their work. This structure includes site-essential, site-by-design, field-based and remote-by-design jobs. The occupancy type that you are assigned is determined by the nature and responsibilities of your role:
Site-essential roles require 100% of shifts onsite at your assigned facility. Site-by-design roles may be eligible for a hybrid work model with at least 50% onsite at your assigned facility. For these roles, onsite presence is considered an essential job function and is critical to collaboration, innovation, productivity, and a positive Company culture. For field-based and remote-by-design roles the ability to physically travel to visit customers, patients or business partners and to attend meetings on behalf of BMS as directed is an essential job function.
Supporting People with Disabilities
BMS is dedicated to ensuring that people with disabilities can excel through a transparent recruitment process, reasonable workplace accommodations/adjustments and ongoing support in their roles. Applicants can request a reasonable workplace accommodation/adjustment prior to accepting a job offer. If you require reasonable accommodations/adjustments in completing this application, or in any part of the recruitment process, direct your inquiries to adastaffingsupport@bms.com . Visit careers.bms.com/ eeo -accessibility to access our complete Equal Employment Opportunity statement.
Candidate Rights
BMS will consider for employment qualified applicants with arrest and conviction records, pursuant to applicable laws in your area.
If you live in or expect to work from Los Angeles County if hired for this position, please visit this page for important additional information: https://careers.bms.com/california-residents/
Data Protection
We will never request payments, financial information, or social security numbers during our application or recruitment process. Learn more about protecting yourself at https://careers.bms.com/fraud-protection .
Any data processed in connection with role applications will be treated in accordance with applicable data privacy policies and regulations.
If you believe that the job posting is missing information required by local law or incorrect in any way, please contact BMS at TAEnablement@bms.com . Please provide the Job Title and Requisition number so we can review. Communications related to your application should not be sent to this email and you will not receive a response. Inquiries related to the status of your application should be directed to Chat with Ripley.
R1605305 : Associate Director, Data ScienceSee All 12 Data Science Engineer Jobs in New Jersey
Find roles in New Jersey that match your experience and apply in just a few clicks.
Find Data Science Engineer JobsData Science Engineer Jobs by City in New Jersey
Where New Jersey roles are concentrated, by current openings.
Data Science Engineer Job Market in New Jersey
A snapshot from current New Jersey openings, updated as new roles post.
Who's Hiring



Top Industries Hiring
- Education
- Technology & Software
- Consulting & Professional Services
What New Jersey Employers Look For
The qualifications that appear most often in data science engineer jobs across New Jersey.
- Bachelor's or master's degree in computer science, statistics, or a related quantitative field
- Proficiency in Python and SQL for data manipulation, modeling, and pipeline development
- Hands-on experience building and deploying machine learning models in production environments
- Familiarity with cloud platforms such as AWS, Azure, or Google Cloud for data engineering workflows
- Experience with big data frameworks including Apache Spark, Kafka, or similar distributed systems
- Strong communication skills to translate complex analytical findings for non-technical New Jersey stakeholders
Data Science Engineer Jobs in New Jersey: Frequently Asked Questions
How do you become a data science engineer in New Jersey?
There is no state-issued license required to work as a data science engineer in New Jersey. Most employers look for a bachelor's degree in computer science, mathematics, or statistics, with a master's degree increasingly preferred at larger pharma, finance, and telecom firms. Building a portfolio of deployed machine learning projects and earning cloud certifications from AWS or Google strengthens applications significantly at New Jersey's major technology and life sciences employers.
How much do data science engineers make in New Jersey?
Data science engineers in New Jersey earn a median of about $135,280 a year, based on May 2025 Bureau of Labor Statistics wage data, ranging from around $80,720 for the lowest 10% to over $203,950 for the top 10%. Pay rises with experience, specialty, and employer.
Which companies hire data science engineers in New Jersey?
Employers hiring data science engineers in New Jersey right now include Merck, AbbVie, and Fiserv, based on current listings on Migrate Mate as of August 2026. New Jersey's concentration of pharmaceutical headquarters, financial services firms, and global telecommunications companies makes it one of the more active states for this role year-round.
Which New Jersey cities have the most data science engineer jobs?
Princeton, New Jersey, and Camden have the most data science engineer openings in New Jersey. Newark and the surrounding area anchor hiring through financial services and logistics firms, Princeton draws heavily from pharmaceutical and biotech campuses in the Route 1 corridor, and Parsippany reflects the large corporate technology and telecom presence concentrated in Morris County.
Are there remote data science engineer jobs in New Jersey?
Yes, and more than most fields. About 100% of data science engineer openings tied to New Jersey are remote or hybrid as of August 2026, reflecting how well the analytical and engineering work translates to distributed environments. Roles focused on model development and data pipeline work tend to be the most remote-friendly, while positions requiring close collaboration with lab or on-site infrastructure teams lean hybrid.
How can I get hired as a data science engineer in New Jersey with little or no experience?
The most realistic entry path is through a data analyst or junior data engineer role at one of New Jersey's large pharma or financial services employers, then transitioning into data science engineering work after demonstrating applied skills. Companies like Johnson and Johnson and Cognizant run new-graduate programs and rotational technology tracks that place candidates without deep experience into analytics teams. Building a portfolio of machine learning projects and earning a cloud associate certification gives candidates a concrete edge in these programs.
Where can I find and apply to data science engineer jobs in New Jersey?
You can find and apply to data science engineer jobs in New Jersey on Migrate Mate, which lists current openings across the state. Search the available roles, find the ones that fit your background and location, and apply directly through each listing.
See All 12 Data Science Engineer Jobs in New Jersey
Find roles in New Jersey that match your experience and apply in just a few clicks.
Find Data Science Engineer Jobs