Data Science Analyst Jobs
Data Science Analyst jobs are open across technology, finance, healthcare, and retail, from entry-level to senior and lead roles, with specializations in predictive modeling, business intelligence, and machine learning engineering. 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.
Data Science Analyst Jobs by Experience Level
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Find Data Science Analyst JobsData Science Analyst Job Market
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 data science analyst jobs.
- Proficiency in Python or R for data analysis and statistical modeling
- Strong SQL skills for querying and manipulating large relational datasets
- Experience with data visualization tools such as Tableau or Power BI
- Bachelor's degree in statistics, computer science, mathematics, or a related field
- Familiarity with machine learning libraries such as scikit-learn or TensorFlow
- Experience communicating analytical findings clearly to non-technical stakeholders
Tips for Your Data Science Analyst Job Search
Quantify model impact on your resume
Recruiters for data science analyst roles want to see outcomes, not just tools. Replace 'built predictive models' with the business result: how much churn you reduced, revenue you influenced, or processing time you cut. Specific numbers make your resume stand out in applicant stacks.
Tailor your portfolio to the industry
A portfolio project in e-commerce demand forecasting won't land the same way at a hospital system. Swap or reframe one project to match the domain you're targeting. Hiring managers in healthcare or finance respond more to domain-relevant examples than technically impressive but unrelated work.
Filter openings by required stack, not just title
Data science analyst roles vary widely in their tooling. Some require Python and SQL, others center on Tableau or Power BI. Search by the specific tools listed in job descriptions you want to land, and deprioritize postings where your stack differs on more than two core requirements.
Apply early to roles that fit
Migrate Mate lists data science analyst openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Prepare for a technical screen before the HR call
Many data science analyst pipelines front-load a take-home SQL or Python assessment before any recruiter conversation. Brush up on window functions, joins, and basic statistical concepts now, so you're not scrambling after you apply. Knowing this stage exists helps you pace your prep correctly.
Negotiate using role-specific comp levers
Data science analyst offers often include components beyond base salary: signing bonuses, equity, conference budgets, and learning stipends. When you receive an offer, ask explicitly about each. Employers who can't move on base often have flexibility on these secondary levers, especially at mid-size tech and fintech firms.
Data Science Analyst Jobs: Frequently Asked Questions
Which companies are hiring the most data science analysts?
The companies hiring the most data science analysts 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 active in technology, financial services, and healthcare sectors.
How many data science analyst jobs are remote?
About 74% of data science analyst openings are fully remote or hybrid as of November 2026, making it one of the more flexible roles in the analytics field. Positions focused on business intelligence, reporting, and predictive modeling tend to have the highest share of remote arrangements, while roles requiring close collaboration with lab or operations teams are more often on-site.
How do you become a data science analyst?
Start by building a foundation in statistics, Python or R, and SQL through coursework, bootcamps, or self-study. Develop a portfolio of projects that show you can clean messy data, build models, and communicate results. Earn a relevant degree or a recognized certification such as Google's Data Analytics Certificate or the IBM Data Science Professional Certificate. Then apply to entry-level analyst or junior data roles to gain professional experience.
Can you get a data science analyst job with little or no experience?
Yes, you can break into data science analyst roles without a formal work history by leading with a strong project portfolio. Build two or three end-to-end projects using publicly available datasets, publish them on GitHub, and explain your methodology clearly. Entry-level titles like junior data analyst, analytics associate, or business intelligence analyst are designed for candidates transitioning into the field, and many employers value demonstrated skill over years of experience.
What does the data science analyst interview process look like?
Most data science analyst pipelines follow four stages: an initial recruiter screen, a technical assessment covering SQL and Python or statistics, a case study or take-home project where you analyze a dataset and present findings, and a final round with the hiring manager and team. The technical screen and case study carry the most weight. Expect to explain your reasoning out loud, not just produce a correct answer.
Where can I find and apply to data science analyst jobs?
You can find and apply to data science analyst jobs on Migrate Mate, which lists current openings from employers across the United States. Search the listings to find roles that match your skills, location preference, and experience level, then apply directly to each one that fits.
See All 743+ Data Science Analyst Jobs
Find roles that match your experience and apply in just a few clicks.
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