Data Analyst

About the Role

Leidos is seeking a highly analytical and curious Data Analyst passionate about turning data into actionable business insights. This hybrid role requires the candidate to be onsite 50% in Fort Worth, TX, and 50% remote, necessitating proximity to the office.

Key Responsibilities

• Extract, clean, transform, and validate data from multiple sources, including relational databases.
• Write efficient SQL queries to retrieve, manipulate, and analyze large datasets.
• Develop Python-based data analysis workflows for data exploration, modeling, and reporting.
• Perform exploratory data analysis (EDA), including univariate, bivariate, and multivariate analysis.
• Apply statistical methods and predictive modeling techniques such as linear regression and other statistical evaluations.
• Utilize AI and machine learning tools to identify trends, generate insights, and improve analytical processes.
• Build and evaluate machine learning models, including:
• Regression
• Classification
• Clustering
• Decision Trees
• Supervised Learning
• Unsupervised Learning
• Investigate data anomalies and independently determine the root causes behind unexpected results.
• Identify the most relevant data elements, metrics, and business questions without requiring extensive direction.
• Translate complex analytical findings into clear, compelling presentations and recommendations for non-technical stakeholders.
• Develop a deep understanding of the business and industry to ensure analyses align with organizational goals.
• Partner with business leaders to provide data-driven recommendations that support strategic decision-making.

Requirements & Tech Stack

• U.S. Citizenship required.
• Secret clearance or ability to obtain one.
• Bachelor's degree in Data Analytics, Computer Science, Statistics, Mathematics, Engineering, Economics, or a related quantitative field (or equivalent practical experience).
• Strong proficiency in Python for data analysis and automation.
• Advanced SQL skills with experience querying and manipulating relational databases.
• Experience cleaning, transforming, and preparing data for analysis.
• Solid understanding of statistics and data analysis methodologies.
• Working knowledge of machine learning concepts and algorithms, including regression, classification, clustering, decision trees, supervised learning, and unsupervised learning.
• Familiarity with Large Language Models (LLMs), AI tools, and their practical application in data analysis.
• Ability to perform exploratory data analysis and communicate meaningful insights from complex datasets.
• Excellent analytical, critical thinking, and problem-solving skills.
• Ability to work independently, prioritize competing tasks, and investigate issues with minimal supervision.
• Strong verbal and written communication skills with the ability to explain technical concepts to non-technical audiences.

Preferred Qualifications

• Experience with data visualization tools such as Power BI, Tableau, or Looker.
• Experience using cloud-based data platforms (AWS, Azure, or Google Cloud).
• Familiarity with version control systems such as Git.
• Experience working with business intelligence, analytics, or AI-driven decision support environments.