Randstad Federal is searching for a Data Scientist to support an active need over with the DEA. This role will be 100% remote but they need someone local to the DMV area (DC Metro). You will be tasked with helping develop and work with data analysis and visualization for the DEA and help increase the DEA's productivity of data usage within the agency.
This role is open to 1099 or W2 candidates only. Randstad will provide 401k match, medical, dental and vision insurance for those who qualify.
**Due to government clearance requirements you must be a US Citizen to obtain the clearance.**
I cannot work with 3rd party C2C vendors
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.
