2

Entry Level Data Analyst Fintech Jobs in Texas (NOW HIRING)

Job Title: Entry-Level Data Analyst Summary We are looking for a motivated Entry-Level Data Analyst to join our analytics team. The candidate will help collect, process, and analyze data to support ...

... within fintech or a related consumer-facing industry (e.g., banking, credit cards, lending ... Strong proficiency in at least one programming language for data analysis (e.g., Python, R)

Data analyst I

Austin, TX · On-site

$25 - $28/hr

1-3 years' experience in data analysis Strong Microsoft Excel skills (must-have) Experience with Power BI Entry-level knowledge of C++ and CSS (nice-to-have, not core) Engineering Technician I Active ...

next page

Showing results 1-20

Entry Level Data Analyst Fintech information

What does an entry level data analyst do in fintech?

An entry level data analyst in fintech is responsible for collecting, cleaning, and interpreting data related to financial products and services. Their work typically involves analyzing large datasets to identify trends, support business decisions, and improve financial products. They may also create dashboards or reports to visualize data findings for other teams. Additionally, entry level analysts often collaborate with engineers, product managers, and senior analysts to ensure data accuracy and relevance. This role provides a strong foundation in both data analysis and the unique challenges of the financial technology sector.

What are some typical projects or tasks that an entry level data analyst in fintech might work on?

As an entry level data analyst in fintech, you’ll often assist with tasks such as cleaning and preparing large financial datasets, creating basic reports and dashboards, and supporting more senior analysts with ad-hoc data requests. You may also help monitor transaction trends for fraud detection, contribute to customer segmentation projects, and automate routine data processes. Collaboration with product, engineering, and compliance teams is common, and you’ll gain valuable exposure to the fast-paced, data-driven decision-making environment typical of fintech companies.

What are the key skills and qualifications needed to thrive as an entry level data analyst in fintech, and why are they important?

To thrive as an Entry Level Data Analyst in Fintech, you need strong analytical skills, a solid grasp of statistics, and a degree in a related field such as mathematics, finance, or computer science. Familiarity with data analysis tools like SQL, Python, and Excel, as well as financial data platforms, is typically expected. Attention to detail, problem-solving abilities, and effective communication are vital soft skills for interpreting data and sharing insights with stakeholders. These skills are important for accurately analyzing complex financial data, driving data-driven decisions, and supporting the company's strategic goals.

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

AspectEntry Level Data Analyst FintechEntry Level Data Scientist Fintech
Required CredentialsBachelor's in Data, Finance, or related field; basic SQL and Excel skillsBachelor's in Data Science, Statistics, or related; programming skills in Python/R; some certifications
Work EnvironmentData analysis teams within fintech companies, focusing on reporting and dashboardsData science teams, working on predictive models and advanced analytics
Employer & Industry UsageCommon in fintech firms for operational insightsLess common at entry level, more in research and development roles

Entry Level Data Analyst Fintech roles focus on interpreting data, creating reports, and supporting decision-making with basic analytics. Entry Level Data Scientist Fintech positions involve more advanced statistical modeling and programming. While both roles require a strong foundation in data concepts, data scientists typically need additional technical skills and certifications. The analyst role is more accessible for beginners, whereas data scientist roles are more specialized and technical.

What are the most commonly searched types of Data Analyst Fintech jobs in Texas?

The most popular types of Data Analyst Fintech jobs in Texas are:

What are popular job titles related to Entry Level Data Analyst Fintech jobs in Texas?

For Entry Level Data Analyst Fintech jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Entry Level Data Analyst Fintech jobs in Texas look for?

The top searched job categories for Entry Level Data Analyst Fintech jobs in Texas are:

What cities in Texas are hiring for Entry Level Data Analyst Fintech jobs?

Cities in Texas with the most Entry Level Data Analyst Fintech job openings:

Infographic showing various Entry Level Data Analyst Fintech job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Entry-Level Data Analyst

Dhalite Inc.

Dallas, TX • On-site

Other

Posted 13 days ago


Job description

Job Title: Entry-Level Data Analyst


Summary

We are looking for a motivated Entry-Level Data Analyst to join our analytics team. The candidate will help collect, process, and analyze data to support business decisions. This role is ideal for entry level candidates who want to start a career in data analytics.

Responsibilities

Collect and organize data from different data sources.
Clean and prepare datasets for analysis.
Analyze data to identify trends and insights.
Create dashboards and visual reports using Microsoft Power BI
Write SQL queries to extract data from databases like MySQL
Prepare weekly or monthly performance reports.
Support senior analysts with data analysis projects.


Qualifications

Bachelor s degree in Data Science, Computer Science, Economics,
0 2 years of experience or relevant internships in business intelligence, data analysis, or reporting
Familiarity with at least one data visualization tool
Basic knowledge of statistics
Strong analytical and problem-solving skills
Good communication skills to present data insights clearly
Attention to detail and ability to work with large datasets