Responsibilities
- Interpret and analyze data using exploratory mathematic and statistical techniques based on the scientific method.
- Coordinate research and analytic activities utilizing various data points (unstructured and structured) and employ programming to clean, massage, and organize the data.
- Experiment against data points, provide information based on experiment results and provide previously undiscovered solutions to command data challenges.
- Coordinate with Data Engineers to build Data environments providing data identified by other data professionals.
- Apply and develop scientific methodology, statistics, and algorithms to discover and frame relevant problems, hypotheses, and opportunities.
- Develop predictive and prescriptive modeling, natural language processing (NLP), Robotic Process Automation (RPA), text mining and processing, clustering, forecasting methods, and other advanced statistical techniques.
- Design and automate processes to facilitate the manipulation and analysis of data. Manage and integrate data across dissimilar data sets. Analyze large-scale structured and unstructured data.
- Use frameworks such as Spark and Hadoop to conduct large-scale data processing. Perform statistical modeling and create data visualizations using products like Tableau, Microsoft Power BI and R Shiny.
- Research, design, and implement algorithms to solve complex problems. Program using R, Python (NumPy, SciPy, Pandas) or similar analytical languages.
- Perform data engineering, data processing and modeling techniques using cloud-based data management, data science, and ML platforms such as Databricks, IBM Cloud Pak, Cloudera, and Snowflake.
- Communicate complex concepts and hypothesis to a non-technical audience through digital storytelling.
- Be capable of instructing others on the use of Data Science practices and capabilities.
Basic qualifications
- A minimum of 6 years of hands-on Data Science experience is required.
- A Bachelor's degree in a STEM field is required.
- Proficiency in one or more programming languages (Java, C++, Python, R, etc.)
- Demonstrated experience applying data science methods to real-world data problems.
- Proficiency in Agile Development and GIT Operations
- Secret Clearance minimum – Top Secret is preferred with SCI eligibility.
Preferred qualifications
- Master's degree in Operations Research, Industrial Engineering, Applied Mathematics, Statistics, Physics, Computer Science, or related fields.
- Top Secret Clearance with SCI Eligibility
Tags & focus areas
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