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Trainee Fintech Data Scientist Jobs (NOW HIRING)

As a key member of the Data Science team, the data scientist will deploy data-driven exploratory ... A voice in the future of fintech * Always-on learning and development * Collaborative work ...

As a key member of the Data Science team, the data scientist will deploy data-driven exploratory ... A voice in the future of fintech * Always-on learning and development * Collaborative work ...

As a key member of the Data Science team, the data scientist will deploy data-driven exploratory ... A voice in the future of fintech * Always-on learning and development * Collaborative work ...

As a key member of the Data Science team, the data scientist will deploy data-driven exploratory ... A voice in the future of fintech * Always-on learning and development * Collaborative work ...

Data Scientist (AHL)

Tempe, AZ ยท On-site

$140K - $160K/yr

Since 2002, Achieve has grown into one of the largest private consumer fintech unicorns in the U.S ... As a Data Scientist (potential uplevel to Sr. Data Scientist for the right experience) , you'll ...

Senior Data Scientist

New York, NY ยท On-site

$170K - $220K/yr

Senior Data Scientist About Current Current is a leading U ... S. fintech serving people who have been overlooked by traditional banks. We are one of the fastest ...

NY ยท On-site

Who we are Moniepoint is a global fintech building modern financial services for millions of people ... If you want to build our data science function from the ground up, work with one of Africa ...

Senior Data Scientist

New York, NY ยท On-site

$170K - $220K/yr

Senior Data Scientist About Current Current is a leading U ... S. fintech serving people who have been overlooked by traditional banks. We are one of the fastest ...

A minimum of 7 years industry experience in data science; previous experience in a marketplace or fintech company is a plus * Strong and relevant experience with advanced experimentation and ...

... trainee measurement aids when required for training of new or upgraded equipment due to a major system modification. Qualifications Required Qualifications: * Bachelor's Degree in Data Science or ...

Staff Data Scientist

San Francisco, CA ยท On-site

$170K - $225K/yr

A minimum of 7 years industry experience in data science; previous experience in a marketplace or fintech company is a plus * Strong and relevant experience with advanced experimentation and ...

Master's or PhD in Computer Science, Data Science, Machine Learning, AI, or related field. * 8+ ... Experience working in fintech, payments, banking, or fraud/risk environments. * Background in ...

Showing results 21-40

Trainee Fintech Data Scientist information

See salary details

$37.5K

$122.7K

$196.5K

How much do trainee fintech data scientist jobs pay per year?

As of Sep 14, 2026, the average yearly pay for trainee 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 is a trainee fintech data scientist?

A Trainee Fintech Data Scientist is an entry-level professional who works with financial technology (fintech) companies to analyze and interpret complex financial data. This role involves learning to use data science tools and techniques such as machine learning, programming, and statistical analysis to solve business problems in areas like risk assessment, fraud detection, and customer insights. Trainees typically work under the supervision of experienced data scientists to gain hands-on experience and develop their technical and domain expertise in the fintech sector.

What kinds of projects and collaborations can a trainee fintech data scientist expect to be involved in during their first year?

As a Trainee Fintech Data Scientist, you'll typically work on real-world data projects such as analyzing transaction patterns, detecting fraud, or building predictive models for credit scoring. You'll collaborate closely with experienced data scientists, software engineers, and business analysts, often participating in agile teams and cross-functional meetings. It's common to have mentorship opportunities and structured training sessions to help you ramp up on both technical skills and domain knowledge. Over time, you'll gain experience presenting your findings to both technical and non-technical stakeholders, which is key for career growth in fintech.

What are the key skills and qualifications needed to thrive as a trainee fintech data scientist, and why are they important?

To thrive as a Trainee Fintech Data Scientist, you need a solid grounding in statistics, data analysis, and programming (often with Python or R), typically supported by an academic background in a quantitative field. Familiarity with data visualization tools, SQL databases, and introductory machine learning libraries is highly beneficial, as is exposure to fintech platforms or certifications like Data Science or Fintech Foundations. Strong analytical thinking, attention to detail, and effective communication skills help you interpret data insights and collaborate with cross-functional teams. These competencies are crucial for extracting meaningful value from complex financial data and driving innovation in a rapidly evolving fintech landscape.

What is the difference between Trainee Fintech Data Scientist vs Junior Data Analyst?

AspectTrainee Fintech Data ScientistJunior Data Analyst
Required CredentialsTypically a degree in data science, computer science, or related field; some certifications beneficialOften a degree in statistics, mathematics, or related field; certifications are optional
Work EnvironmentFintech companies, startups, or financial institutions; focus on developing models and algorithmsVarious industries including finance, retail, or healthcare; focus on data reporting and analysis
Employer & Industry UsageCommonly used in fintech for developing predictive models and algorithmsUsed across industries for data reporting, visualization, and basic analysis

The Trainee Fintech Data Scientist focuses on developing advanced models and algorithms within the fintech industry, often requiring programming skills and statistical knowledge. In contrast, a Junior Data Analyst primarily handles data reporting and visualization tasks. While both roles require a background in data-related fields, the trainee data scientist role emphasizes machine learning and model development, making it more technical and specialized.

More about Trainee Fintech Data Scientist jobs

What cities are hiring for Trainee Fintech Data Scientist jobs?

Cities with the most Trainee 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 Trainee Fintech Data Scientist jobs?

States with the most job openings for Trainee Fintech Data Scientist jobs include:

What are popular job titles related to Trainee Fintech Data Scientist jobs?

For Trainee Fintech Data Scientist jobs, the most frequently searched job titles are:

Infographic showing various Trainee Fintech Data Scientist job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 84% Full Time, 12% Part Time, and 2% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $122,738 per year, or $59 per hour.

Data Scientist Lead

Milwaukee, WI โ€ข On-site

Worldpay, Inc.
Technology, Communication and Mediaย โ€ขย 10K+ employees

Full-time

Posted 18 days ago


Key responsibilities

  • Lead the design, development, validation, deployment, and monitoring of advanced analytics, machine learning, and AI solutions that drive measurable business outcomes.

  • Analyze and prepare data for modeling by assembling datasets from standard and novel data sources, and incorporate them into analytical solutions.

  • Communicate analytical findings through presentations, dashboards, visualizations, and self-service tools to support decision-making.


Job description

Job Description

Are you curious, motivated, and forward-thinking? At FIS you'll have the opportunity to work on some of the most challenging and relevant issues in financial services and technology. Our talented people empower us, and we believe in being part of a team that is open, collaborative, entrepreneurial, passionate and above all fun.

About the role:

As a key member of the Data Science team, the data scientist will deploy data-driven exploratory analysis as well as predictive models and AI solutions to solve business problems across the financial services industry, particularly in Risk, Fraud, Marketing, and Portfolio Management. Following the machine learning lifecycle, the data scientist should be able to convert the results into actionable product recommendations to present internally and externally.

What you'll be doing:

  • Lead the design, development, validation, deployment, and monitoring of advanced analytics, machine learning, and AI solutions that drive measurable business outcomes.
  • Leverage expertise in data structures and algorithms to analyze and prepare data for modeling, assembling datasets from both standard and novel data sources and incorporate them into end-to-end analytical solutions.
  • Apply advanced machine learning, predictive analytics, natural language processing (NLP), and emerging AI techniques (GenAI, Agentic etc.) to solve complex business problems across the payments and financial services ecosystem.
  • Design and execute experiments, hypothesis testing frameworks, and statistical analyses to evaluate business strategies, product enhancements, and operational improvements.
  • Establish and promote best practices in data science, machine learning, feature engineering, experimentation, model governance, and MLOps throughout the organization.
  • Communicate complex analytical findings through compelling storytelling, executive-ready presentations, dashboards, visualizations and self-service analytics tools. that drive informed decision-making.
  • Stay current on industry trends in machine learning, AI, Generative AI, and financial services analytics; bring relevant innovations to the team.

What you bring:

  • Master's degree or higher in Mathematics, Computer Science, Engineering, Operations Research, Statistics, or a related quantitative discipline.
  • 5+ years of experience developing and deploying end-to-end machine learning, predictive analytics, and data science solutions within the Payments, Banking, or Financial Services industry.
  • Strong proficiency in Python and SQL; experience with big data technologies such as Spark, PySpark, a plus.
  • Hands-on experience with data wrangling, feature engineering, and model development using libraries such as Pandas, NumPy, Scikit-learn, Matplotlib, Seaborn, or Plotly.
  • Demonstrated experience building and deploying machine learning models in a production or near-production environment.
  • Proficiency with data visualization and business intelligence tools (e.g., Tableau or equivalent).
  • Strong analytical thinking and problem-solving skills; ability to translate ambiguous business problems into rigorous analytical frameworks.
  • Ability to work collaboratively across product, engineering, and business teams.

Nice to have:

  • Experience within the Payments, Banking, or Financial Services industry.
  • Hands-on experience with the Databricks platform, including MLflow, Model Registry, collaborative notebooks, and MLOps workflows.
  • Experience deploying cloud-native machine learning solutions, particularly within AWS environments.
  • Working familiarity with emerging advancements in Transformer Models and Agentic AI technologies.
  • Knowledge of model governance, regulatory compliance, and MLOps best practices within regulated financial services environments.

What we offer you:

A career at FIS is more than just a job. It's the chance to shape the future of fintech. At FIS, we offer you:

  • A voice in the future of fintech
  • Always-on learning and development
  • Collaborative work environment
  • Opportunities to give back
  • Competitive salary and benefits


Privacy Statement

FIS is committed to protecting the privacy and security of all personal information that we process in order to provide services to our clients. For specific information on how FIS protects personal information online, please see the Online Privacy Notice.

EEOC Statement

FIS is an equal opportunity employer. We evaluate qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, marital status, genetic information, national origin, disability, veteran status, and other protected characteristics. The EEO is the Law poster is available here supplement document available here


For positions located in the US, the following conditions apply. If you are made a conditional offer of employment, you will be required to undergo a drug test. ADA Disclaimer: In developing this job description care was taken to include all competencies needed to successfully perform in this position. However, for Americans with Disabilities Act (ADA) purposes, the essential functions of the job may or may not have been described for purposes of ADA reasonable accommodation. All reasonable accommodation requests will be reviewed and evaluated on a case-by-case basis.

Sourcing Model

Recruitment at FIS works primarily on a direct sourcing model; a relatively small portion of our hiring is through recruitment agencies. FIS does not accept resumes from recruitment agencies which are not on the preferred supplier list and is not responsible for any related fees for resumes submitted to job postings, our employees, or any other part of our company.

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