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Fintech Data Science Jobs in Boston, MA (NOW HIRING)

Senior Data Scientist

Boston, MA ยท Hybrid

$95K - $166K/yr

As a Senior Data Science at Nasdaq, you will join a specialized team of AI researchers pushing the ... Work experience in a corporate environment or finance/fintech industry * Experience with Deep ...

Senior Data Scientist

Boston, MA ยท On-site

$95K - $166K/yr

As a Senior Data Science at Nasdaq, you will join a specialized team of AI researchers pushing the ... Work experience in a corporate environment or finance/fintech industry * Experience with Deep ...

Degree in MIS, Computer Science, or related technical degrees are not required, but are a plus ... data using AI, seamless integration capabilities, and proprietary automation technology. Fintech is ...

Help Desk Support

Beverly, MA ยท On-site

$45K/yr

Degree in MIS, Computer Science, or related technical degrees are not required, but are a plus ... data using AI, seamless integration capabilities, and proprietary automation technology. Fintech is ...

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Fintech Data Science information

See Boston, MA salary details

$40.7K

$133.3K

$213.5K

How much do fintech data science jobs pay per year?

As of Aug 22, 2026, the average yearly pay for fintech data science in Boston, MA is $133,327.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,000.00 and $147,700.00 per year, depending on experience, location, and employer.

What is a fintech data scientist?

A Fintech Data Scientist is a professional who uses data analysis, machine learning, and statistical techniques to solve problems and create value within the financial technology (fintech) industry. They work with large amounts of financial data to develop predictive models, detect fraud, assess risk, and optimize financial products or services. Their expertise combines knowledge of finance, programming, and advanced analytics to help fintech companies make data-driven decisions and innovate in areas such as payments, lending, and investment. Fintech Data Scientists often collaborate with engineers, product managers, and business stakeholders to deliver actionable insights that drive business growth.

What are the key skills and qualifications needed to thrive as a fintech data scientist?

To thrive as a Fintech Data Scientist, you need a strong background in statistics, machine learning, and programming (often with a degree in computer science, mathematics, or a related field). Familiarity with tools such as Python, R, SQL, cloud computing platforms, and experience with financial data modeling or relevant certifications are typically required. Strong problem-solving skills, attention to detail, and effective communication are important soft skills that set top professionals apart. These skills and qualities are vital for extracting actionable insights from complex financial data, driving innovation, and ensuring regulatory compliance in the fast-evolving fintech industry.

How do fintech data scientists typically collaborate with product and engineering teams to develop new financial products?

In fintech, data scientists often work closely with product managers and engineering teams throughout the lifecycle of a financial product. They analyze user data and market trends to provide actionable insights during the product design phase, and collaborate with engineers to implement machine learning models into the product infrastructure. Regular cross-functional meetings and agile workflows are common, allowing data scientists to iterate on models based on feedback and evolving requirements. This collaborative environment ensures that data-driven solutions are robust, scalable, and aligned with business goals.

What is the difference between Fintech Data Science vs Fintech Data Analyst?

AspectFintech Data ScienceFintech Data Analyst
Required SkillsAdvanced statistical, programming, and machine learning skillsData interpretation, reporting, and basic analytics
CertificationsData Science certifications, programming coursesData analysis or business intelligence certifications
Work EnvironmentDeveloping models, algorithms, and predictive analyticsData reporting, dashboards, and data cleaning
Industry UsageCreating predictive models for risk, fraud detection, and customer insightsGenerating reports, supporting decision-making with data

Fintech Data Science involves building complex models and applying machine learning techniques, requiring advanced skills and certifications. Fintech Data Analysts focus on interpreting data, creating reports, and supporting business decisions with less technical complexity. Both roles are essential in the fintech industry but differ in technical depth and responsibilities.

Is data science good for fintech?

Data science is highly valuable in fintech, as it enables the development of algorithms for risk assessment, fraud detection, and personalized financial services. Fintech companies often rely on data analysis, machine learning, and statistical modeling to improve decision-making and customer experience. Skills in programming, data manipulation, and financial knowledge are essential for data scientists in this field.

Is fintech data science a high paying career?

Fintech data science is generally a high-paying career due to the demand for advanced analytics and machine learning skills in financial technology companies. Salaries often depend on experience, education, and technical expertise in tools like Python, R, and SQL, with senior roles earning significantly more. The field offers competitive compensation compared to many other data science roles across industries.
Infographic showing various Fintech Data Science job openings in Boston, MA as of August 2026, with employment types broken down into 94% Full Time, and 6% Contract. Highlights an 64% In-person, 18% Hybrid, and 18% Remote job distribution, with an average salary of $133,327 per year, or $64.1 per hour.

Principal Data Scientist, GTM Data Science

Socket.dev

Boston, MA โ€ข On-site

$182 - $242.60/hr

Other

Posted 20 days ago


Job description

About SimpliSafe

We're a high-tech home security company that's passionate about protecting the life you've built and our mission of keeping Every Home Secure. And we've created a culture here that cares just as deeply about the career you're building. Ours is a no ego culture of collaboration and innovation where those seeking their next challenge can find big opportunities and make a huge impact on the lives of all those who we protect. We don't just want you to work here. We want you to grow and thrive here.

Why are we hiring?

Well, we're growing and thriving. So, we need smart, talented, and humble people who share our values to join us as we disrupt the home security space and relentlessly pursue our mission of keeping Every Home Secure.

Role Overview

As Principal Data Scientist, GTM Data Science, you will report to the Senior Director of Data Science and serve as a senior technical leader for growth, marketing, customer lifecycle, and personalization. You will shape the strategy and production systems that help SimpliSafe acquire, retain, and grow subscriber relationships while improving the customer experience.

What We're Looking For
  • Deep expertise in marketing science, customer personalization, lifecycle modeling, and applied machine learning.
  • Strong hands-on experience building and deploying machine learning solutions that have driven measurable business outcomes in production.
  • Experience developing models and decision systems for customer acquisition, conversion, retention, segmentation, personalization, lifetime value, and next-best-action use cases.
  • Strong understanding of experimentation, causal inference, incrementality measurement, and marketing effectiveness.
  • Significant experience with MLOps, model deployment, model monitoring, and distributed compute environments.
  • Proficiency with Python, SQL, Databricks, AWS SageMaker, Spark, MLflow, and modern cloud data platforms.
  • Experience designing scalable data and feature pipelines for production ML systems.
  • Ability to operate as a senior individual contributor: setting technical direction, influencing roadmaps, mentoring others, and driving execution across teams.
  • Strong communication skills, with the ability to explain complex modeling concepts to technical and non-technical stakeholders.
  • Typically 6+ years of experience in data science, machine learning, applied statistics, or a related field, or equivalent demonstrated expertise.
Preferred Qualifications
  • Hands-on experience with advanced ML techniques such as Gradient Boosted Trees, neural networks, and transformer-based models.
  • Experience applying modern AI/ML techniques, including unstructured data or advanced signal integration, in production environments.
  • Experience designing or deploying agentic AI solutions that orchestrate models, tools, data, and workflows to automate or augment GTM decision-making.
  • Experience building recommendation, personalization, real-time decisioning, or next-best-action systems.
  • Experience in subscription, ecommerce, smart home, security, telecommunications, insurance, fintech, or other customer lifecycle-driven businesses.
  • Advanced degree in Computer Science, Statistics, Machine Learning, Economics, Applied Mathematics, Engineering, or a related quantitative field.
What Values You\'ll Share
  • Customer Obsessed - Building deep empathy for our customers, putting them at the core of our work, and developing strong, long-term relationships with them.
  • Aim High - Always challenging ourselves and others to raise the bar.
  • No Ego - Maintaining a "no job too small" attitude, and an open, inclusive and humble style.
  • One Team - Taking a highly collaborative approach to achieving success.
  • Lift As We Climb - Investing in developing others and helping others around us succeed.
  • Lean & Nimble - Working with agility and efficiency to experiment in an often ambiguous environment.
What We Offer

A mission- and values-driven culture and a safe, inclusive environment where you can build, grow and thrive

A comprehensive total rewards package that supports your wellness and provides security for SimpliSafers and their families (For more information on our total rewards please click here )

Free SimpliSafe system and professional monitoring for your home.

Employee Resource Groups (ERGs) that bring people together, give opportunities to network, mentor and develop, and advocate for change.

The target annual base pay range for this role is $182,000 to $242,600

This target annual base pay range represents our good-faith estimate of what we expect to pay for this role. We use a market-based compensation approach to set our target annual base pay ranges and make adjustments annually. We carefully tailor individual compensation packages, including base pay, taking into consideration employees\' job-related skills, experience, qualifications, work location, and other relevant business factors.

Beyond base pay, we offer a Total Rewards package that may include pa

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