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Data Science Summer Intern
$54,080 - 95,680
Navy Federal Credit Union
Heritage Oaks Drive 5500, Pensacola
$54,080 - 95,680
Requirements
Must:
We are looking for candidates who are currently pursuing an undergraduate or graduate degree in Data Science, Computer Science, Information Systems, Business Analytics, or a related field. Applicants should have experience with Python (particularly Pyspark) and SQL, as well as familiarity with cloud technologies such as Microsoft Azure and Databricks. Experience in data visualization tools like PowerBI or Tableau is also essential. We value excellent communication and presentation skills and seek individuals who can navigate ambiguity in data and analytical projects. A curious and energetic mindset is strongly desired.
Responsibilities
As a Summer Associate, you will support our data science and machine-learning initiatives. Your role will involve retrieving, analyzing, and modeling data within our Azure Databricks environment. You will also package your results into executive-level presentations and share your findings with senior management.
Description
The Summer Associate Program is a 12-week internship that runs from May 2026 to August 2026. You will work on impactful projects that contribute to our understanding of member engagement with various deposit products, including certificates of deposits, money market accounts, checking accounts, IRAs, and ESAs. One representative project could entail building a machine-learning propensity model to predict the likelihood of members maintaining excess deposits in checking accounts and initiating recurring transfers to a money market account. Additionally, you may perform complex analytical tasks using large datasets to uncover insights about member behavior and support feature engineering efforts. At Navy Federal, we offer more than just a job; we provide a meaningful career experience within a dynamic and committed culture. Our competitive pay, generous benefits, and recognition of our team's contributions set us apart as one of the best places to work. We encourage you to make our mission your passion. We are proud to be recognized as one of the best employers across a variety of categories and remain committed to equal opportunity for all qualified applicants. This means your candidacy will be considered without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status. Please note that we may fill this position at a higher or lower grade level based on business needs, and assessments may be required for candidates. Job postings may close earlier or be extended depending on the volume of qualified applicants. Furthermore, we evaluate market data to establish competitive salary ranges commensurate with your experience, location, and market position. We expect all employees to remain cognizant of and adhere to our policies and regulations, including those related to the Bank Secrecy Act.
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You can find Data Engineer salaries in the United States here.
How many Data Engineer jobs are in the United States?
Currently, there are 885 Data openings. Check also: Spark jobs, Snowflake jobs, Kafka jobs, Hadoop jobs - all with salary brackets.
Is the US a good place for Data Engineers?
The US is one of the best countries to work as a Data Engineer. It has a vibrant startup community, growing tech hubs and, most important: lots of interesting jobs for people who work in tech.
Which companies are hiring for Data Engineer jobs in the United States?
Sperasoft, Bain Magique, Archon Systems Inc, Journey Freight International inc, Puter Technologies Inc., Ontario One Call, HAPLY Robotics Inc. among others, are currently hiring for Data roles in the United States.
The company with most openings is Leidos as they are hiring for 88 different Data Engineer jobs in the United States. They are probably quite committed to find good Data Engineers.
The company with most openings is Leidos as they are hiring for 88 different Data Engineer jobs in the United States. They are probably quite committed to find good Data Engineers.