ASRC Federal is seeking a Data Scientist to support the DEA's Diversion Division.  

Work arrangement: Remote

Clearance: Public Trust (must be a US Citizen to meet contract requirements) and successfully complete a government background investigation.  

Summary:  The ideal candidate is a highly skilled professional who uses their expertise in data analysis, statistical modeling, and machine learning to extract insights and solve complex problems.

Responsibilities:

Data Analysis and Modeling:
• Collect, clean, and preprocess large datasets from various sources.
• Apply statistical techniques and data mining algorithms to analyze data and identify patterns, trends, and relationships.
• Develop and implement predictive models, machine learning algorithms, and statistical models to solve business problems and generate actionable insights.

Machine Learning and AI:
• Design and develop machine learning models and algorithms to solve specific business challenges.
• Train, validate, and optimize models using appropriate techniques such as cross-validation and hyperparameter tuning.
• Deploy models into production environments and monitor their performance.

Data Visualization and Reporting:
• Communicate complex data analysis results and insights to non-technical stakeholders through clear and visually appealing data visualizations, reports, and presentations.
• Collaborate with cross-functional teams to understand their data needs and provide data-driven recommendations.

Data Exploration and Feature Engineering:
• Conduct exploratory data analysis to understand the characteristics and quality of the data.
• Identify and engineer relevant features from raw data to improve model performance and accuracy.

Collaboration and Communication:
• Collaborate with data engineers, software developers, and domain experts to gather requirements, define data needs, and implement data-driven solutions.
• Communicate findings, methodologies, and insights to both technical and non-technical audiences effectively.

Requirements: 

• Strong knowledge of statistical analysis, machine learning algorithms, and data modeling techniques.
• Proficiency in programming languages such as Python or R, and experience with data manipulation and analysis libraries (e.g., pandas, NumPy, scikit-learn).
• Experience with data visualization tools (e.g., Tableau, matplotlib, ggplot) to effectively communicate insights.
• Familiarity with big data technologies (e.g., Hadoop, Spark) and cloud platforms (e.g., AWS, Azure) is desirable.
• Strong problem-solving skills, critical thinking, and the ability to work on complex projects independently.
• Excellent communication and presentation skills to convey complex concepts to both technical and non-technical stakeholders.

Education/Experience:

• Bachelor's or Master's degree in a quantitative field such as Computer Science, Statistics, Mathematics, or related disciplines. A Ph.D. is a plus. (4 years' experience is the equivalent to a bachelor’s degree, 8 years is equivalent to a Master’s)
• 5+ years of relevant work experience in data analytics.