Data Scientist
Listed on 2026-01-24
-
IT/Tech
Data Scientist, Data Analyst, Machine Learning/ ML Engineer, AI Engineer
TLA is seeking an experienced and curious Data Scientist to join our team and transform complex data into actionable insights that drive strategic business decisions. The ideal candidate will combine expertise in statistics, programming, and machine learning to solve real-world problems and enable smarter business processes through analytics. You will work cross-functionally to define requirements, build predictive models, and communicate findings to technical and non‑technical stakeholders.
Key Responsibilities- Data Collection & Preparation:
Collect, clean, and preprocess large, complex datasets from various internal and external sources to ensure data integrity and usability. - Exploratory Data Analysis (EDA):
Perform in-depth exploratory data analysis to identify patterns, trends, anomalies, and uncover hidden opportunities. - Model Development & Implementation:
Design, develop, test, and validate statistical and machine learning models (e.g., classification, regression, clustering) to forecast trends, optimize operations, and improve product offerings. - Data Storytelling & Communication:
Translate complex technical findings and data insights into clear, compelling narratives and visualizations (reports, dashboards, presentations) for key decision‑makers across the organization. - Collaboration:
Partner with data engineers, software developers, and business stakeholders (marketing, product, operations) to implement data‑driven solutions and integrate models into production environments. - Experimentation:
Design and execute A/B testing and other experiments to measure the effectiveness of new initiatives and continuously improve model performance.
Stay up-to-date with the latest tools, technologies, and methodologies in the data science field, including AI and large language models (LLMs), to drive innovation.
Requirements- Education:
Bachelor’s or Master’s degree in a quantitative field such as Statistics, Mathematics, Computer Science, Engineering, or a related discipline. - Experience:
3+ years of hands‑on industry experience in a data science or machine learning role. - Programming
Languages:
Strong proficiency in Python or R for data analysis and statistical modeling, and advanced knowledge of SQL for data extraction and manipulation. - Machine Learning:
Practical experience applying a range of machine learning techniques and algorithms (e.g., scikit‑learn, Tensor Flow, PyTorch). - Data Visualization:
Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib, Seaborn) to present data insights effectively. - Analytical
Skills:
Strong analytical and problem‑solving abilities, with an emphasis on critical thinking and the scientific method. - Communication:
Excellent verbal and written communication skills with the ability to explain complex data science concepts to non‑technical audiences.
- Microsoft Certified:
Azure Data Scientist Associate - IBM Data Science Professional Certificate
- Certified Analytics Professional (CAP)
- AWS Certified Machine Learning – Specialty
- Tensor Flow Developer Certificate
We offer a competitive and comprehensive benefits package including:
- Competitive salary and performance bonuses
- Medical, dental, and vision coverage
- Paid time off and federal holidays
- 401(k) with company match
- Education and certification reimbursement
- Training and professional development opportunities
- Employee referral bonuses and team events
At TLA
, we build solutions that matter—supporting national security missions through technology innovation, collaboration, and excellence. Our team is passionate about leveraging modern technologies to deliver impactful, mission‑focused outcomes for our customers.
TLA is proud to be an Equal Opportunity Employer
. We celebrate diversity and are committed to creating an inclusive environment for all employees.
Seniority level: Mid‑Senior level
Employment type: Full‑time
Job function: Other
Industries: IT Services and IT Consulting
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