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Entry Level Fintech Data Scientist Jobs (NOW HIRING)

This is an entry level Data Scientist Role for a person who is self motivated and has a passion to innovate and work on cutting edge technology. Qualifications Candidate should have experience in ...

This is an entry level Data Scientist Role for a person who is self motivated and has a passion to innovate and work on cutting edge technology. Qualifications Candidate should have experience in ...

Data Scientist I - Remote

$84.90K - $108.20K/yr

... and an integrated fintech solutions provider. The company serves more than 4,000 financial ... The data scientist will collect, process, and analyze large data sets to uncover trends, patterns ...

Senior Data Scientist

Boston, MA · 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 ...

Senior Data Scientist

Boston, MA · 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 ...

Associate Data Scientist

Morgantown, WV · On-site

$60.70K - $61.20K/yr

Working alongside data scientists, ML engineers, and clinical analysts, this role applies ... This is an entry-level to early-career role for candidates who have curiosity about healthcare data ...

$60.70K - $61.20K/yr

Working alongside data scientists, ML engineers, and clinical analysts, this role applies ... This is an entry-level to early-career role for candidates who have curiosity about healthcare data ...

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Junior Data Scientist

Miami, FL · On-site

$30 - $35/hr

Job Title: Jr. Data Scientist Location: Miami, FL Employment type ... Fulltime Duration: 2 years Exp: 1-4 years(Entry level) Educational Qualification: Master's Degree ...

People Data Scientist Purpose and Scope/General Summary: We are seeking a People Data Scientist to ... entry-level employees. The ability to relate to different types of people and understand their ...

Description People Data Scientist Purpose and Scope/General Summary: We are seeking a People Data ... entry-level employees. The ability to relate to different types of people and understand their ...

People Data Scientist Purpose and Scope/General Summary: We are seeking a People Data Scientist to ... entry-level employees. The ability to relate to different types of people and understand their ...

Description Position at JBS USA People Data Scientist Purpose and Scope/General Summary: We are ... entry-level employees. The ability to relate to different types of people and understand their ...

This position is responsible for performing entry level analysis of program-related data, including building and maintaining databases and spreadsheets. The Data Scientist will collaborate with ...

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Entry Level Fintech Data Scientist information

See salary details

$37.5K

$122.7K

$196.5K

How much do entry level fintech data scientist jobs pay per year?

As of May 31, 2026, the average yearly pay for entry level fintech data scientist in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an Entry Level Fintech Data Scientist, and why are they important?

To thrive as an Entry Level Fintech Data Scientist, you need a solid background in statistics, programming (Python or R), and foundational knowledge of finance or economics, often supported by a relevant degree. Familiarity with data analysis tools such as SQL, machine learning frameworks like scikit-learn, and experience with cloud platforms or financial databases are typically required. Strong problem-solving skills, attention to detail, and effective communication help you interpret data insights and present findings to both technical and non-technical stakeholders. These competencies are crucial for developing accurate data models and delivering actionable insights in the fast-paced fintech industry.

What are some common challenges faced by entry-level data scientists in fintech, and how can they overcome them?

Entry-level data scientists in fintech often encounter challenges such as working with highly sensitive financial data, navigating complex regulatory requirements, and keeping up with rapidly evolving technologies. It can also be daunting to translate data findings into actionable business insights for stakeholders who may not have a technical background. To overcome these challenges, it's helpful to develop strong communication skills, seek mentorship from experienced colleagues, and stay updated on industry best practices and compliance standards. Regular collaboration with cross-functional teams, such as engineering and product, is also essential for building a solid foundation and advancing in the fintech sector.

What does an Entry Level Fintech Data Scientist do?

An Entry Level Fintech Data Scientist works with financial data to build models, analyze trends, and help companies make data-driven decisions. They typically use programming languages like Python or R, along with statistical and machine learning techniques, to extract insights from large financial datasets. Their day-to-day tasks may include cleaning data, developing predictive models, visualizing results, and collaborating with finance and engineering teams. This role is crucial for improving financial products, detecting fraud, and optimizing business strategies in the fintech industry.

What is the difference between Entry Level Fintech Data Scientist vs Entry Level Data Analyst?

AspectEntry Level Fintech Data ScientistEntry Level Data Analyst
Required CredentialsBachelor's in Data Science, Computer Science, or related field; knowledge of programming languages like Python or RBachelor's in Statistics, Mathematics, or related field; proficiency in Excel, SQL, and basic data visualization tools
Work EnvironmentFinancial technology companies, banks, or fintech startups; focus on developing predictive models and algorithmsVarious industries including finance, marketing, and healthcare; focus on data reporting and basic analysis
Employer & Industry UsageCommonly employed in fintech firms to build data-driven products and servicesWidely used across industries for business insights and reporting

In summary, an Entry Level Fintech Data Scientist typically requires programming skills and focuses on building models within fintech companies, while an Entry Level Data Analyst emphasizes data reporting and visualization across various industries. Both roles serve different analytical needs but share foundational data skills.

More about Entry Level Fintech Data Scientist jobs
What cities are hiring for Entry Level Fintech Data Scientist jobs? Cities with the most Entry Level Fintech Data Scientist job openings:
What are the most commonly searched types of Fintech Data Scientist jobs? The most popular types of Fintech Data Scientist jobs are:
What states have the most Entry Level Fintech Data Scientist jobs? States with the most job openings for Entry Level Fintech Data Scientist jobs include:
Infographic showing various Entry Level Fintech Data Scientist job openings in the United States as of May 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $122,738 per year, or $59 per hour.
Data Scientist

Full-time

Posted 14 days ago


Job description

The Data Scientist works closely with Retail Technology, Media and Account Services teams to provide predictive modeling of Marketing, Direct & Digital Efforts. We are looking for a motivated Data Scientist and analytical thought leader. This is a rare opportunity to be part of a diverse and newly expanded analytics department and a great fit for a predictive modeler with a desire to impact business results.

Responsibilities

  • Apply specialized technical knowledge and expertise to perform reviews relating to the full life cycle of models, information technology applications, or risk management/analysis used across the company.
  • Collaborate and share knowledge with teams across the media organization, as appropriate. Build and maintain relationships with business partners at the manager and staff levels.
  • Use data analysis, mining, and migration techniques for enhanced targeting, audience segmentation, clustering, profiling, and regression analysis
  • Identify digital placement-level strengths and weaknesses across simultaneous campaigns and geographies
  • Develop and maintain internal automated reporting tools, documents, scoring systems, and dashboards for on-going and post-campaign reporting
  • Coordinate cross-functional reviews to discuss region- and campaign-specific findings and actionable recommendations for digital media campaigns built on various CPM, CPC, CPE, and CPA models
  • Identify and facilitate resolution of tagging issues in coordination with Traffic and Production teams focused on site-side tracking, reporting, and implementation
  • Provide client-facing/non-technical recommendations and insights, both in a written and verbal manner, that provide understandable and actionable optimizations.
  • Work with Media, Strategic Intelligence and Account Services teams to develop measurement plans to deliver on campaign and client objectives

Requirements

  • Bachelor’s degree in related field
  • Entry-Level and/or College Internship experience 
  • Must demonstrate the ability to successfully develop and run analytics (scripts) using specialized tools and platforms, specifically, R, Python, SQL, and/or SAS.
  • Experience applying data synthesis, mining and regression techniques for enhanced targeting, audience segmentation, clustering, profiling, and insightful recommendations
  • Advanced knowledge of Microsoft Excel
  • General understanding of digital advertising, digital media strategy, ad placement type, placement-level insight, and standard media metrics is preferred
  • Experience with data orchestration tools such as Annalect Omni is preferred
  • Excellent verbal, written and interpersonal communication skills
  • Ability to work independently and as part of a team
  • Ability to manage multiple projects simultaneously while meeting deadlines
  • Regression modeling focusing on maximizing yield while measuring the diminishing returns of ad spend at scale for thousands of locations.
  • Data storytelling and presentation

Required Skills
Required Experience