Senior Data Science Engineer Jobs
Senior Data Science Engineer jobs are open across technology, finance, healthcare, and e-commerce, from mid-level to staff and principal, with specializations in machine learning infrastructure, large-scale data pipelines, and applied modeling. Find a role that fits from the openings below and apply directly.
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Join our dynamic team at an innovative insurance software company! We are seeking a Professional Services Consultant with a strong background in analytics within the insurance industry, ideally holding ACAS or near-ACAS designation. In this role, you will be instrumental in supporting our clients’ usage of our software for data extraction and analysis, developing and reviewing statistical models, and implementing effective pricing strategies.
What you’ll do:
Develop and maintain predictive models to assess risk and customer demand, guiding pricing strategies across various lines of business.
Utilize machine learning techniques and programming languages such as Python and R to enhance analytics capabilities.
Communicate complex technical results clearly and effectively, tailoring presentations for diverse audiences.
Demonstrate software functionality and provide training to new users, ensuring a smooth onboarding process.
Requirements:
You’ll do it using:
Extensive experience in the insurance industry, specifically in analytics and predictive modeling.
Proficiency in machine learning methods and programming languages (Python and R).
Exceptional communication skills, with a knack for presenting technical information in an accessible manner.
Strong ability to engage clients and provide valuable insights through data analysis.
You’ll excel by:
Focusing on the art of the possible
Communicating with honesty, candour, and respect
Collaborating seamlessly with colleagues across the company
Being resourceful and creative
Acting with empathy
You’ll love it because:
This is an incredibly impactful role in the organization.
You will have the opportunity to work in a successful, fast-moving, mission-driven company.
You will have growth opportunities.
You will collaborate with other professional and enthusiastic team members.
Earnix has competitive benefits with an all-for-one mentality.
Salary Range:
$78,000-142,000 per year
Position Intro:
Earnix is the premier provider of mission-critical, cloud-based intelligent decisioning across pricing, rating, underwriting, and product personalization. These fully-integrated solutions provide ultra-fast ROI and are designed to transform how global insurers and banks are run by unlocking value across all facets of the business. Earnix has been innovating for insurers and banks since 2001 with customers in over 35 countries across six continents and offices in the Americas, Europe, Asia Pacific, and Israel.
Join our dynamic team at an innovative insurance software company! We are seeking a Professional Services Consultant with a strong background in analytics within the insurance industry, ideally holding ACAS or near-ACAS designation. In this role, you will be instrumental in supporting our clients’ usage of our software for data extraction and analysis, developing and reviewing statistical models, and implementing effective pricing strategies.
What you’ll do:
Develop and maintain predictive models to assess risk and customer demand, guiding pricing strategies across various lines of business.
Utilize machine learning techniques and programming languages such as Python and R to enhance analytics capabilities.
Communicate complex technical results clearly and effectively, tailoring presentations for diverse audiences.
Demonstrate software functionality and provide training to new users, ensuring a smooth onboarding process.
Requirements:
You’ll do it using:
Extensive experience in the insurance industry, specifically in analytics and predictive modeling.
Proficiency in machine learning methods and programming languages (Python and R).
Exceptional communication skills, with a knack for presenting technical information in an accessible manner.
Strong ability to engage clients and provide valuable insights through data analysis.
You’ll excel by:
Focusing on the art of the possible
Communicating with honesty, candour, and respect
Collaborating seamlessly with colleagues across the company
Being resourceful and creative
Acting with empathy
You’ll love it because:
This is an incredibly impactful role in the organization.
You will have the opportunity to work in a successful, fast-moving, mission-driven company.
You will have growth opportunities.
You will collaborate with other professional and enthusiastic team members.
Earnix has competitive benefits with an all-for-one mentality.
Salary Range:
$78,000-142,000 per year
Position Intro:
Earnix is the premier provider of mission-critical, cloud-based intelligent decisioning across pricing, rating, underwriting, and product personalization. These fully-integrated solutions provide ultra-fast ROI and are designed to transform how global insurers and banks are run by unlocking value across all facets of the business. Earnix has been innovating for insurers and banks since 2001 with customers in over 35 countries across six continents and offices in the Americas, Europe, Asia Pacific, and Israel.
Senior Data Science Engineer Jobs by Experience Level
Top Cities Hiring Senior Data Science Engineers
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Who's Hiring
- Amazon27
- Capital One27
- Information Technology Senior Management Forum18
- Deloitte15
- Meta14
Top Industries Hiring
- Technology & Software29
- Education21
- Retail8
- Insurance7
- Banking & Financial Services7
What Employers Look For
The qualifications that appear most often in senior data science engineer jobs.
- 5 or more years of experience in data science, machine learning, or a related engineering discipline
- Proficiency in Python and experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn
- Hands-on experience designing and deploying production-grade machine learning pipelines
- Strong command of distributed computing tools including Spark, Databricks, or equivalent platforms
- Experience with cloud platforms such as AWS, Google Cloud, or Azure for data and model infrastructure
- Bachelor's or master's degree in computer science, statistics, mathematics, or a closely related field
Tips for Your Senior Data Science Engineer Job Search
Quantify your modeling impact clearly
Hiring managers want to see what your models actually moved. Replace vague claims with specifics: latency reduced, prediction accuracy improved, or revenue attributed to a deployed system. Concrete outcomes separate senior candidates from mid-level ones faster than any credential.
Tailor your resume to the stack
Senior data science engineer roles vary widely by tooling. One company runs Spark on Databricks, another on Kubernetes with Ray. Scan each job posting for the exact stack and mirror that language in your resume so automated screening and hiring managers both register the match.
Target roles by architecture ownership
Some postings want someone to build pipelines, others want someone to own the full ML platform. Read the responsibilities section carefully and apply to roles where the scope matches what you can lead independently, not just contribute to.
Apply early to roles that fit
Migrate Mate lists senior 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.
Prepare a system design walkthrough
Most senior-level loops include a machine learning system design round. Practice walking through feature stores, serving infrastructure, monitoring, and retraining pipelines out loud. Interviewers are testing whether you think end-to-end, not just whether you can tune a model.
Negotiate scope before you negotiate compensation
At this seniority level, title scope and team ownership vary more than the pay band. Before your final conversation, clarify what decisions you'd own, whether you'd manage engineers, and how success gets measured. Misaligned scope costs more than a lower offer over time.
Senior Data Science Engineer Jobs: Frequently Asked Questions
Which companies are hiring the most senior data science engineers?
The companies hiring the most senior data science engineers right now include Amazon, Capital One, and Information Technology Senior Management Forum, with the largest share of openings in California, New York, and Virginia, based on current listings on Migrate Mate as of November 2026. Demand is especially high at companies scaling ML infrastructure across cloud-native platforms.
How many senior data science engineer jobs are remote?
About 74% of senior data science engineer openings are fully remote or hybrid as of November 2026, making this one of the more flexible senior technical roles in the market. ML platform engineering and research-adjacent positions tend to carry the highest share of fully remote arrangements compared to roles tied to real-time production systems.
How do you become a senior data science engineer?
You reach the senior level by owning production machine learning systems end-to-end, not just building models in notebooks. That means shipping models that run reliably in production, learning pipeline orchestration and feature engineering at scale, and contributing to architectural decisions. Most engineers get there by taking on increasing infrastructure ownership over several years and demonstrating that their work directly influences business outcomes.
Can you get hired as a senior data science engineer with limited experience?
It's possible if you can demonstrate depth in a specific area that is hard to find. Strong open-source contributions, a portfolio of production ML projects, or deep expertise in a specialized domain like recommendation systems or computer vision can offset a shorter work history. Targeting startups or smaller teams where scope is broader and seniority expectations are more flexible also improves your chances significantly.
What does the senior data science engineer interview process look like?
The process typically includes a recruiter screen, a technical phone interview covering ML concepts and coding, a machine learning system design round, and a full loop with several panel interviews. The system design round is the stage where senior candidates are most frequently filtered out. Expect to walk through how you would architect a complete ML system, including data ingestion, training, serving, and monitoring, rather than just solve a modeling problem.
Where can I find and apply to senior data science engineer jobs?
You can find and apply to senior data science engineer jobs on Migrate Mate, which lists current openings from across the United States in one place. Find roles that match your experience and specialization, then apply directly to each listing.
See All 741+ Senior Data Science Engineer Jobs
Find roles that match your experience and apply in just a few clicks.
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