Data Science Engineer Jobs
Data Science Engineer jobs are open across technology, healthcare, finance, and e-commerce, from entry-level to principal and staff levels, with specializations in machine learning infrastructure, MLOps, and real-time data pipelines. Find a role that fits from the openings below and apply directly.
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About AbbVie
AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on LinkedIn, Facebook, Instagram, X and YouTube.
Job Description
The Clinical Data Strategy and Operations (CDSO) DMO Lead or Clinical Data Scientist (CDS) serves as the data management domain expert and key strategic partner to the clinical study team. This role owns the data collection strategy, drives implementation, oversees data quality delivery, and supports on-time achievement of key study milestones. As the Data Operations single point of contact for cross-functional stakeholders, the DMO Lead or CDS applies strong project management, risk oversight, and continuous process optimization to enable data quality, inspection readiness, and successful trial delivery.
Responsibilities:
- Serves as the CDSO data management subject matter expert and single point of contact for assigned studies, owning data collection, data cleaning, and database lock strategies to enable high-quality, inspection-ready study delivery.
- Leads risk-based and continuous data review strategies from study start-up through database lock, leveraging centralized monitoring, statistical review, and clinical data science methodologies to proactively identify and mitigate study risks.
- Triages data quality standards across studies to identify trends, drive site-level actions through effective cross-functional communication, and maintain data currency in support of timely, reliable study decisions.
- Interprets clinical and operational data, quality metrics, predictive signals, and dashboard outputs to develop data-driven recommendations that strengthen study execution, risk management, patient safety oversight, and quality across the clinical development lifecycle.
- Contributes to defining, managing, and monitoring data-driven protocol deviations.
- Defines and manages study data flow and triages issues from raw EDC data through mapped SDTM data, partnering with internal technology teams, service providers, and vendors to drive timely mitigation and support end-to-end data integrity.
- Performs data mining and custom analytics, gathers business requirements for study dashboards, and generates operational metrics that support study decisions.
- Ensures adherence to federal and applicable local regulations, Good Clinical Practices (GCPs), ICH Guidelines, AbbVie SOPs, and functional quality standards; stays abreast of evolving guidance.
- Influences cross-functional stakeholders without direct authority, aligning clinical, statistical, medical, safety, regulatory, technology, and vendor organizations around data-driven decisions and clinical data science strategies.
- Leads CDSO innovation and process improvement initiatives and participates in cross-functional efforts that improve operational effectiveness, scalability, and study delivery quality.
- Coaches and mentors team members.
Qualifications
- Bachelor’s degree in business, management information systems, computer science, life sciences or equivalent. Masters preferred.
- Must have 6+ years of pharma / clinical research / data management / health care experience or 8+ years of project management experience (and / or applicable work experience).
- In-depth understanding of clinical trial processes and clinical technology. Management of a clinical trial from initiation through to completion in a lead role is preferred.
- Demonstrated performance as a functional leader
- Demonstrated ability to influence others without direct authority
- Demonstrated ability to successfully coach / mentor in a matrix environment
- Demonstrated effective communication skills
- Demonstrated effective analytical skills
Additional Information
Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law:
- The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future.
- We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees.
- This job is eligible to participate in our long-term incentive programs.
Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company’s sole and absolute discretion, consistent with applicable law.
AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community. Equal Opportunity Employer/Veterans/Disabled.
US & Puerto Rico only - to learn more, visit https://www.abbvie.com/join-us/equal-employment-opportunity-employer.html
US & Puerto Rico applicants seeking a reasonable accommodation, click here to learn more:
https://www.abbvie.com/join-us/reasonable-accommodations.html
About AbbVie
AbbVie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people's lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on LinkedIn, Facebook, Instagram, X and YouTube.
Job Description
The Clinical Data Strategy and Operations (CDSO) DMO Lead or Clinical Data Scientist (CDS) serves as the data management domain expert and key strategic partner to the clinical study team. This role owns the data collection strategy, drives implementation, oversees data quality delivery, and supports on-time achievement of key study milestones. As the Data Operations single point of contact for cross-functional stakeholders, the DMO Lead or CDS applies strong project management, risk oversight, and continuous process optimization to enable data quality, inspection readiness, and successful trial delivery.
Responsibilities:
- Serves as the CDSO data management subject matter expert and single point of contact for assigned studies, owning data collection, data cleaning, and database lock strategies to enable high-quality, inspection-ready study delivery.
- Leads risk-based and continuous data review strategies from study start-up through database lock, leveraging centralized monitoring, statistical review, and clinical data science methodologies to proactively identify and mitigate study risks.
- Triages data quality standards across studies to identify trends, drive site-level actions through effective cross-functional communication, and maintain data currency in support of timely, reliable study decisions.
- Interprets clinical and operational data, quality metrics, predictive signals, and dashboard outputs to develop data-driven recommendations that strengthen study execution, risk management, patient safety oversight, and quality across the clinical development lifecycle.
- Contributes to defining, managing, and monitoring data-driven protocol deviations.
- Defines and manages study data flow and triages issues from raw EDC data through mapped SDTM data, partnering with internal technology teams, service providers, and vendors to drive timely mitigation and support end-to-end data integrity.
- Performs data mining and custom analytics, gathers business requirements for study dashboards, and generates operational metrics that support study decisions.
- Ensures adherence to federal and applicable local regulations, Good Clinical Practices (GCPs), ICH Guidelines, AbbVie SOPs, and functional quality standards; stays abreast of evolving guidance.
- Influences cross-functional stakeholders without direct authority, aligning clinical, statistical, medical, safety, regulatory, technology, and vendor organizations around data-driven decisions and clinical data science strategies.
- Leads CDSO innovation and process improvement initiatives and participates in cross-functional efforts that improve operational effectiveness, scalability, and study delivery quality.
- Coaches and mentors team members.
Qualifications
- Bachelor’s degree in business, management information systems, computer science, life sciences or equivalent. Masters preferred.
- Must have 6+ years of pharma / clinical research / data management / health care experience or 8+ years of project management experience (and / or applicable work experience).
- In-depth understanding of clinical trial processes and clinical technology. Management of a clinical trial from initiation through to completion in a lead role is preferred.
- Demonstrated performance as a functional leader
- Demonstrated ability to influence others without direct authority
- Demonstrated ability to successfully coach / mentor in a matrix environment
- Demonstrated effective communication skills
- Demonstrated effective analytical skills
Additional Information
Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law:
- The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future.
- We offer a comprehensive package of benefits including paid time off (vacation, holidays, sick), medical/dental/vision insurance and 401(k) to eligible employees.
- This job is eligible to participate in our long-term incentive programs.
Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company’s sole and absolute discretion, consistent with applicable law.
AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community. Equal Opportunity Employer/Veterans/Disabled.
US & Puerto Rico only - to learn more, visit https://www.abbvie.com/join-us/equal-employment-opportunity-employer.html
US & Puerto Rico applicants seeking a reasonable accommodation, click here to learn more:
https://www.abbvie.com/join-us/reasonable-accommodations.html
Data Science Engineer Jobs by Experience Level
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Find Data Science Engineer JobsData Science Engineer Job Market
Who's Hiring
- Amazon33
- Capital One18
- Walmart16
- Deloitte12
- TikTok10
Top Industries Hiring
- Technology & Software45
- Education23
- Retail13
- Banking & Financial Services13
- Insurance9
What Employers Look For
The qualifications that appear most often in data science engineer jobs.
- Proficiency in Python with experience building production-grade data and ML pipelines
- Hands-on experience with distributed computing frameworks such as Apache Spark or Flink
- Experience deploying and monitoring machine learning models in cloud environments like AWS, GCP, or Azure
- Familiarity with MLOps tooling including feature stores, model registries, and workflow orchestrators
- Bachelor's or master's degree in computer science, data engineering, statistics, or a related field
- Experience with containerization and orchestration tools such as Docker and Kubernetes
Tips for Your Data Science Engineer Job Search
Separate your ML and engineering work
Hiring managers want to see both sides of your work. Structure your resume into distinct sections for model development and for infrastructure, pipelines, or deployment engineering. Conflating the two makes it harder for reviewers to assess either.
Target openings that match your stack
Data science engineer job descriptions vary widely in tooling. Filter for roles that name the exact frameworks you know well, whether that is PyTorch, Spark, or Kubeflow. Applying to a strong stack match beats applying broadly to a dozen misaligned roles.
Apply early to roles that fit
Migrate Mate lists data science engineer openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Showcase end-to-end project ownership
Interviewers routinely ask how you took a model from prototype to production. Prepare a clear narrative for at least one project covering data ingestion, model training, deployment, and monitoring. Vague answers about 'building models' without the deployment story consistently hurt candidates at this level.
Quantify pipeline performance, not just accuracy
Accuracy metrics impress data scientists, but data science engineers are expected to own system performance too. Lead with latency improvements, throughput gains, or cost reductions your pipelines achieved. Those numbers stand out to engineering managers who are evaluating your systems thinking.
Negotiate on scope, not just compensation
After an offer, ask specifically which part of the ML lifecycle you will own at hire versus six months in. Scope ambiguity is the top source of dissatisfaction in this role. Clarifying it upfront also signals the kind of systems-level thinking that makes hiring managers more confident in their offer.
Data Science Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most data science engineers?
The companies hiring the most data science engineers right now include Amazon, Capital One, and Walmart, with the largest share of openings in California, New York, and Virginia, based on current listings on Migrate Mate as of September 2026. Demand is especially concentrated in technology, financial services, and healthcare data platforms.
How many data science engineer jobs are remote?
About 65% of data science engineer openings are fully remote or hybrid as of September 2026, making it one of the more flexible engineering roles to search. Sub-areas like MLOps, feature engineering, and model serving infrastructure tend to have the highest share of remote-eligible positions, since those workflows are well-suited to asynchronous, distributed team structures.
How do you become a data science engineer?
Start by building strong fundamentals in Python and SQL, then layer in distributed data processing frameworks like Spark. Work on end-to-end projects that take a model from raw data through training, deployment, and monitoring. Develop familiarity with cloud platforms and containerization. Contributing to open-source data infrastructure projects or publishing documented pipelines on a public portfolio accelerates your path into the role.
Can you break into data science engineering without much experience?
Yes, but you need to substitute depth for breadth early on. Build one well-documented end-to-end ML pipeline project that demonstrates data ingestion, training, deployment, and observability. Roles titled junior data engineer or ML engineer are common entry points where companies expect less production experience. Certifications in a major cloud platform can strengthen applications when your professional history is thin.
What does the data science engineer interview process look like?
Most processes run three to five rounds. An initial recruiter screen is followed by a technical phone interview covering Python, SQL, or system design basics. The core rounds typically include a take-home or live coding assessment on pipeline design, a machine learning systems design interview, and a final round with engineering leadership. Some employers add a presentation of a past project as a fifth stage.
Where can I find and apply to data science engineer jobs?
You can find and apply to data science engineer jobs on Migrate Mate, which lists current openings from employers across the United States. Find the roles that fit your experience and stack, then apply directly to each listing from the results on this page.
See All 653+ Data Science Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
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