About
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.
Innovation:
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.
Qualifications
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, TensorFlow, 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.
Preferred Certifications
Microsoft Certified: Azure Data Scientist Associate
IBM Data Science Professional Certificate
Certified Analytics Professional (CAP)
AWS Certified Machine Learning – Specialty
TensorFlow Developer Certificate
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.
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
TLA is proud to be an
Equal Opportunity Employer . We celebrate diversity and are committed to creating an inclusive environment for all employees.
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Languages
- English
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