Senior Data Scientist - FFPP-8757
Innovative Systems & Solutions•Annapolis Junction, MD
•$200,000 - $215,000
About The Position
A data scientist will develop machine learning, data mining, statistical and graph-based algorithms to analyze and make sense of datasets; prototype or consider several algorithms and decide upon final model based on suitable performance metrics; build models or develop experiments to generate data when training or example datasets are unavailable; generate reports and visualizations that summarize datasets and provide data-driven insights to customers; partner with subject matter experts to translate manual data analysis into automated analytics; implement prototype algorithms within production frameworks for integration into analyst workflows.
Requirements
- This position requires in-scope poly, within 7 years.
- Bachelor's degree from an accredited college or university in a quantitative discipline (e.g.,statistics, mathematics, operations research, engineering or computer science).
- Five (5) years of experience analyzing datasets and developing analytics
- Five (5) years of experience programming with data analysis software such as R, Python, SAS, or MATLAB.
- An additional four (4) years of experience in software development, cloud development, analyzing datasets,or developing descriptive, predictive, and prescriptive analytics can be substituted for aBachelor's degree.
- A PhD from an accredited college or university in a quantitative discipline can be substituted for four (4) years of experience.
- Programming Languages: Proficiency in programming languages such as Python and R is crucial for data manipulation, analysis, and implementing algorithms. Python is favored for its simplicity and extensive libraries (likeNumPy and pandas), while R is preferred for statistical analysis and data visualization.
- Statistical Analysis: A strong foundation in statistics and probability is necessary for analyzing data accurately and making informed decisions. Understanding concepts like regression analysis, hypothesis testing, and statistical distributions is essential.
- Machine Learning: Knowledge of machine learning algorithms and frameworks (such as TensorFlow and Scikit-Learn) is vital for building predictive models and automating decision-making processes.
- Data Wrangling: The ability to clean and organize complex datasets is critical. Data wrangling involves transforming raw data into a usable format, which is often time-consuming but necessary for effective analysis.
- Database Management: Familiarity with SQL and database management systems (like PostgreSQL and MongoDB) is essential for extracting and manipulating data stored in relational databases.
- Data Visualization: Skills in data visualization tools (such as Tableau and Matplotlib) help communicate findings effectively. Creating charts, graphs, and dashboards is crucial for making data understandable to stakeholders.
Responsibilities
- Produce data visualizations that provide insight into dataset structure and meaning
- Work with subject matters experts (SMEs) to identify important information in raw data and develop scripts that extract this information from a variety of data formats (e.g., SQL tables,structured metadata, network logs)
- Incorporate SME input into feature vectors suitable for analytic development and testing
- Translate customer qualitative analysis process and goals into quantitative formulations that are coded into software prototypes
- Develop and implement statistical, machine learning, and heuristic techniques to create descriptive, predictive, and prescriptive analytics
- Develop statistical tests to make data-driven recommendations and decisions
- Develop experiments to collect data or models to simulate data when required data is unavailable
- Develop feature vectors for input into machine learning algorithms
- Identify the most appropriate algorithm for a given dataset and tune input and model parameters
- Evaluate and validate the performance of analytics using standard techniques and metrics(e.g. cross validation, ROC curves, confusion matrices)
- Oversee the development of individual analytic efforts and guide team in analytic development process
- Guide analytic development toward solutions that can scale to large datasets
- Partner with software engineers and cloud developers to develop production analytics
- Develop and train machine learning systems based on statistical analysis of data characteristics to support mission automation
Benefits
- 401(k) with matching contributions
- Health, Dental, and Vision coverage
- Prescription drug plans
- Employer-funded Health Savings Account (HSA)
- Mental health resources
- Life and AD&D insurance
- Short-Term and Long-Term Disability coverage
- Business travel and expense reimbursement
- Employee referral program with cash bonuses
- Employee recognition program
- Tuition and training reimbursement
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What This Job Offers
Job Type
Full-time
Career Level
Senior
