Master's degree in a quantitative discipline or equivalent experience
5+ years in data science, machine learning, or advanced analytics
Strong proficiency in Python and SQL
Hands-on experience with machine learning and statistical analysis
Familiarity with generative AI and large language models
Experience in exploratory analysis and model validation
Strong business communication skills
Responsibilities
Develop and validate predictive and machine-learning models
Lead data science projects from definition to implementation
Perform exploratory data analysis on complex datasets
Identify data-quality and modeling limitations
Design evaluation methods aligned with business objectives
Collaborate with engineering teams to integrate models into applications
Establish monitoring practices for model performance
Benefits
Eligible for medical, dental, and vision benefits
Full-time employment
Onsite work model 4 to 5 days a week
Opportunity to lead innovative data science initiatives
Engagement with cross-functional teams for diverse projects
Full Job Description
Key Details
Compensation: $170,000 - $180,000 with potential Bonus
Location: Arlington, TX
Work Model: ONSITE 4 to 5 Days a week
Benefits: Are eligible to enroll in benefits, including medical, dental, and vision
Employment Type: Full-Time
Work Authorization: Applicants must be currently authorized to work in the United States on a full-time basis; our client will not sponsor applicants for work visas now or in the future
We are seeking an experienced Senior Data Scientist to develop advanced analytics, machine learning, and AI solutions that improve business decisions and performance. This role will lead projects from initial problem definition through modeling, validation, deployment, and ongoing monitoring.
The ideal candidate combines strong technical expertise with practical business judgment and can clearly communicate complex findings to both technical and nontechnical stakeholders.
Key Responsibilities
Develop and validate predictive, forecasting, optimization, statistical, and machine-learning models
Lead data science initiatives from problem definition through production implementation
Perform exploratory data analysis and feature engineering using large, complex datasets
Identify data-quality, measurement, and modeling limitations
Design evaluation methods that reflect business objectives, operational constraints, and potential risks
Partner with engineering and technology teams to integrate models into applications, workflows, and APIs
Establish monitoring practices to evaluate model performance after deployment
Clearly communicate findings, assumptions, uncertainty, and recommendations to business stakeholders
Support cross-functional discovery, architecture, governance, and operational-readiness efforts
Evaluate emerging analytics and AI capabilities for practical business applications
Lead pilot initiatives and help move successful solutions into production
Maintain professional and ethical business practices
Required Qualifications
Master's degree in a quantitative discipline or a bachelor's degree with equivalent professional experience
5+ years of experience in data science, machine learning, advanced analytics, statistics, or a related field
Strong Python and SQL skills
Hands-on experience with machine learning, forecasting, statistical analysis, or optimization
Familiarity with generative AI, large language models, prompt development, context design, and evaluation methods
Experience with exploratory analysis, feature engineering, model validation, experimentation, and version control
Experience partnering with engineering teams to deploy and support models in production
Strong business communication skills and the ability to work effectively with nontechnical subject-matter experts
Ability to work independently, take ownership, and deliver results in a changing environment
Preferred Qualifications
Experience with cloud-based data and machine-learning platforms
Familiarity with model-lifecycle tools and commonly used open-source machine-learning libraries
Experience working with geospatial, document-based, or other unstructured data
Experience developing analytics or AI solutions within a large or complex organization
Experience building new data products, technical capabilities, or solutions from the ground up
Ready to take the next step in your career? Apply today. We're actively interviewing and excited to meet you.
