Job Detail

Data Scientist/Machine Learning Engineer

Data Science and AI Full–time
ID: #19655
Posted: 2026-02-26
Salary

Description

About the position Team CATHEXIS elevates the government contracting experience through rapid response, deep skill, and thoughtful problem-solving and communication. Our core capabilities are our top-tier program and project management, data analytics, and audit services, the backbone of which is our integrated approach to operational excellence. You worked hard to get to where you are. You strive to make every day better than the day before. So do we. Team CATHEXIS operates with an all-in mindset. We are working together to create a company that supports our shared values and individual goals. Our values are centered around Respect, Engagement, Customer Service, Integrity, Teamwork, and Excellence in everything we do for our employees, clients, partners, and communities. We believe success is best when we listen and lead with empathy; model high standards of ethics to provide a rewarding candidate experience; work hard, have fun, and appreciate the strengths we all bring to the team; and empower our employees to create innovative and trusted results. We are looking for a dynamic Data Scientist/ML Engineer to join our team. The Data Scientist/ML Engineer will work directly with data scientists, software engineers, and subject matter experts in the definition of new analytics capabilities able to provide our federal customers with the information they need to make proper decisions and enable their digital transformation. We are proactively building a pipeline of qualified candidates for future opportunities that may arise. If your background aligns with our anticipated needs, a member of our Talent Acquisition team may reach out should a role become available or to proactively screen you for the role. Responsibilities • Research, design, implement, and deploy Machine Learning algorithms for enterprise applications. • Assist and enable federal customers to build their own applications. • Contribute to the design and implementation of new features. Requirements • Bachelor's degree in Computer Science, Electrical Engineering, Statistics, or equivalent fields required. • Minimum 2 years relevant work experience preferred. • Excellent programming skills in Python. • Applied Machine Learning experience (regression and classification, supervised, and unsupervised learning). • Strong mathematical background (linear algebra, calculus, probability, and statistics). • Experience with scalable ML (MapReduce, streaming). • Ability to drive a project and work both independently and in a team. • Smart, motivated, can-do attitude, and seeks to make a difference. • Excellent verbal and written communication. • Real passion for developing team-oriented solutions to complex engineering problems. • Thrive in an autonomous, empowering and exciting environment. • Great verbal and written communication skills to collaborate multi-functionally and improve scalability. • Interest in committing to a fun, friendly, expansive, and intellectually stimulating environment. • Convey highly technical concepts and information in written form to technical and non-technical audiences. • The ability to work on multiple concurrent projects is essential. • Strong self -motivation and the ability to work with minimal supervision. • Must be a team-oriented individual, energetic, result & delivery oriented, with a keen interest on quality and the ability to meet deadlines. • Ability to work in an agile environment. Nice-to-haves • MS or PhD in Computer Science, Electrical Engineering, Statistics, or equivalent fields preferred. • Hands-on experience deploying and operating applications using IaaS and PaaS on major cloud providers, such as Amazon AWS, Microsoft Azure, or Google Cloud Services. • Experience with deep learning, natural language processing, computer vision, or reinforcement learning. Benefits • Performance Bonuses • Medical Insurance • Dental Insurance • Vision Insurance • 401(k) Plan (Traditional and ROTH) • Life Insurance (Basic, Voluntary & AD&D) • Paid Time Off • 11 Federal Holidays • Parental Leave • Commute Benefits • Short Term & Long Term Disability • Training & Development • Wellness Program • Community Outreach Initiatives

Hard Skills 16
Skill Source Confidence
Python llm_hard
100%
Linear Algebra llm_hard
100%
Calculus llm_hard
100%
Probability llm_hard
100%
Statistics llm_hard
100%
Supervised Learning llm_hard
100%
Unsupervised Learning llm_hard
100%
Reinforcement Learning llm_hard
100%
Classification Algorithms llm_hard
100%
Regression Algorithms llm_hard
100%
Deep Learning llm_hard
100%
Computer Vision llm_hard
100%
Google Cloud AI llm_hard
80%
AWS (SageMaker, EC2, S3) llm_hard
80%
Azure ML llm_hard
80%
Distributed Computing llm_hard
80%
Soft Skills 31
Skill Source Confidence
Critical Thinking llm_soft
100%
Working Independently llm_soft
100%
Analytical Thinking llm_soft
100%
Self-Motivation llm_soft
100%
Cross-Functional Communication llm_soft
100%
Explaining Complex Ideas Clearly llm_soft
100%
Technical Writing llm_soft
100%
Written Communication llm_soft
100%
Teamwork llm_soft
100%
Collaboration llm_soft
100%
Problem-Solving llm_soft
100%
Open to Learning llm_soft
100%
Verbal Communication llm_soft
100%
Goal-Oriented llm_soft
80%
Results-Driven llm_soft
80%
Continuous Improvement llm_soft
80%
Positive Attitude llm_soft
80%
Confidence llm_soft
80%
Curiosity llm_soft
80%
Documentation llm_soft
80%
Creative Problem Solving llm_soft
80%
Innovation llm_soft
80%
Adaptability llm_soft
80%
Flexibility llm_soft
80%
Learning Agility llm_soft
80%
Emotional Intelligence llm_soft
80%
Time Management llm_soft
80%
Organization Skills llm_soft
80%
Multitasking llm_soft
80%
Initiative llm_soft
80%
Drive llm_soft
80%
Apply Options
Publisher Direct Link
Teal No Apply
API Logs for this Job
Query Country Status Response ms Created
Data Scientist/Machine Learning Engineer extracted 12965 2026-03-28 10:55
Data Scientist/Machine Learning Engineer classified 432 2026-03-28 10:24
machine learning engineer gb processed 16939 2026-03-28 10:08
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