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Entry Level Bank Data Scientist Jobs (NOW HIRING)

Valley Bank

Data Scientist

Manhattan, NY · On-site

Knowledge and experience in the banking industry and banking systems. * Advanced knowledge of data ... The Data Scientist will have strong collaboration and communication skills to effectively partner ...

Procter & Gamble

Data Scientist

Cincinnati, OH · On-site

$85K - $122K/yr

As a Data Scientist in our organization, you will play a crucial role in disrupting current ... Job Schedule Full time Job Number R000135859 Job Segmentation Entry Level Starting Pay / Salary ...

Proctor & Gamble

Data Scientist

Cincinnati, OH

$85K - $122K/yr

As a Data Scientist in our organization, you will play a crucial role in disrupting current ... Job Schedule Full time Job Number R000135859 Job Segmentation Entry Level Starting Pay / Salary ...

Bank of America

Data Scientist I

Charlotte, NC · On-site

$105K - $193K/yr

At Bank of America, we are guided by a common purpose to help make financial lives better through ... We are the core data scientists building end-to-end production level solutions at scale. The team ...

PNC Bank

As a Data Scientist within PNC's Corporate and Institutional Banking (C&IB) organization, you will be based in Pittsburgh or Philadelphia, PA, Cleveland, OH, Birmingham, AL, Wilmington, DE, Charlotte ...

Publicis Groupe Holdings B.V

Data Scientist

Chicago, IL · On-site

... Bank of America, Best Buy, Kellogg Company, McDonald's, Novartis, Samsung, Visa and more. Overview ... They will work under the guidance of senior data science leaders to deliver impactful, data-driven ...

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Entry Level Bank Data Scientist information

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$37.5K

$122.7K

$196.5K

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

As of Aug 3, 2026, the average yearly pay for entry level bank 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 Bank Data Scientist, and why are they important?

To thrive as an Entry Level Bank Data Scientist, you need a solid background in statistics, data analysis, and programming—often supported by a relevant degree in mathematics, computer science, or a related field. Familiarity with tools like Python, R, SQL, and data visualization platforms, as well as knowledge of financial data systems, is commonly expected. Analytical thinking, attention to detail, and effective communication are crucial soft skills for interpreting data and presenting findings to non-technical stakeholders. These competencies enable accurate data-driven decisions that support banking operations, risk management, and customer insights.

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

AspectEntry Level Bank Data ScientistEntry Level Bank Data Analyst
Required CredentialsBachelor's degree in Data Science, Statistics, or related field; knowledge of programming languages like Python or RBachelor's degree in Finance, Economics, or related field; proficiency in Excel and SQL
Work EnvironmentData-driven teams within banks, focusing on predictive modeling and advanced analyticsOperational teams analyzing financial data, preparing reports, and supporting decision-making
Employer & Industry UsageFinancial institutions, banks, fintech companiesBanking sector, financial services firms

While both roles involve working with financial data, Entry Level Bank Data Scientists focus on developing predictive models and advanced analytics, requiring programming skills and statistical knowledge. Entry Level Bank Data Analysts primarily handle data reporting and basic analysis, emphasizing proficiency in Excel and SQL. Both roles are essential in banking but differ in technical complexity and responsibilities.

What are some common challenges faced by entry-level data scientists in the banking sector, and how can new hires navigate them?

Entry-level data scientists in banking often encounter challenges such as working with highly regulated, sensitive financial data and adapting to legacy systems that may limit tool choices. New hires may also need to quickly learn domain-specific knowledge, like risk modeling or fraud detection. To succeed, it's helpful to proactively seek mentorship from experienced colleagues, participate in cross-functional project meetings to understand business objectives, and invest time in learning about data privacy regulations. Building strong communication skills is also important, as you'll often collaborate with IT, compliance, and business teams to ensure your analyses align with both technical and regulatory requirements.

What does an Entry Level Bank Data Scientist do?

An Entry Level Bank Data Scientist analyzes financial data to help banks make data-driven decisions. Their work often involves cleaning and processing large datasets, building statistical models, and creating reports to identify trends or detect fraud. They collaborate with other teams to improve products, optimize processes, and ensure regulatory compliance. While they may not lead projects, they play a key role in supporting analytics initiatives and learning advanced data science techniques on the job.
More about Entry Level Bank Data Scientist jobs
What are the most commonly searched types of Bank Data Scientist jobs? The most popular types of Bank Data Scientist jobs are:
What states have the most Entry Level Bank Data Scientist jobs? States with the most job openings for Entry Level Bank Data Scientist jobs include:
What job categories do people searching Entry Level Bank Data Scientist jobs look for? The top searched job categories for Entry Level Bank Data Scientist jobs are:
Entry Level Bank Data Scientist jobs near you
Infographic showing various Entry Level Bank Data Scientist job openings in the United States as of July 2026, with employment types broken down into 75% Full Time, and 25% Part Time. Highlights an 100% In-person job distribution, with an average salary of $122,738 per year, or $59 per hour.

Data Scientist

Valley Bank

Manhattan, NY • On-site

Full-time

Posted 10 days ago

Valley Bank rating

7.3

Company rating: 7.3 out of 10

Based on 19 frontline employees who took The Breakroom Quiz

113th of 170 rated banks

Job description

Responsibilities include, but are not limited to:
  • Interpret business needs and requirements and independently perform analysis and/or build reports and dashboards to meet requirements.
  • Translate analysis findings and technical topics, visualize data to explain results to a non-technical business audience and senior management.
  • Identify new data capabilities to enable strategic objectives, partner with data enablement team to build solutions.
  • Interact independently with business partners on data needs and respond to data requests.
  • Perform challenging data queries, reconcile data, analyze results, and form conclusions for senior management.
  • Drive a strong data-driven culture within the company by mentoring data analysts and increasing data capabilities in other internal functions.

Required Skills:
  • Hands-on experience in data modelling, data engineering and data analysis tools such as BI tools, Power BI, SQL, Python (pandas, numpy).
  • Working knowledge in developing reports and dashboards in Power BI or Tableau.
  • Strong communication, organizational and interpersonal skills, as well as the ability to prioritize and execute multiple objectives.
  • Ability to identify key insights and present results to a business audience.
  • Preferred experience in mapping techniques, such as calculating distances and routes, as well as ability to build custom market and demographic maps.
  • Awareness of latest trends in data analytics.
  • Knowledge and experience in the banking industry and banking systems.
  • Advanced knowledge of data structures and the ability to visualize data effectively to communicate to a business audience.
  • The Data Scientist will have strong collaboration and communication skills to effectively partner with other data teams and business partners.

Required Experience:
  • Bachelor's degree in a quantitative discipline, such as Business Analytics, Data Science, Mathematics, Econometrics, Engineering, Sciences.
  • Miniumum of 3 years working in a data analytics role with hands-on experience in wrangling large data sets, conducting data analysis and developing insights from data.
  • Experience working independently with business partners and diverse corporate functions.

Preferred Experience:
  • Master's degree in a quantitative discipline.
  • Financial Services experience and knowledge of Retail/Commercial Banking industry, products, and data highly desired.

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