Staff Data Scientist

Description

About Us

eSimplicity is a modern digital services company that works across government, partnering with our clients to improve the health and lives of millions of Americans, ensure the security of all Americans—from soldiers and veterans to kids and the elderly, and defend national interests on the battlefield. Our engineers, designers, and strategists cut through complexity to create intuitive products and services that courageously equip Federal agencies with solutions to transform today for a better tomorrow for all Americans.

We are looking for a Staff Data Scientist to analyze large amounts of raw information to find patterns that will help our customers make business decisions and meet their mission. We will rely on you to build data products to extract valuable business insights. In this role, you should be highly analytical with a knack for analysis, math, and statistics. We also want to see a passion for machine-learning and research. 

Responsibilities: 

• Develop data-driven solutions explicitly tailored toward the needs of our customer. 
• Utilize analytical, statistical, and programming skills to collect, analyze, and interpret large data sets. 
• Collect data through means such as analyzing business results or by setting up and managing new studies. Create new, experimental frameworks to collect data and custom data models and algorithms to apply to data sets. Identify valuable data sources and build tools to automate data collection. Standardize data ingestion and processing pipelines to scale with increased usage and utilization. 
• Transform data into a new format to make it more appropriate for analysis. 
• Undertake preprocessing of structured and unstructured data. 
• Develop (Analytics, AI/ML) and interpret large dataset engineering: data augmentation, data quality analysis, data analytics (anomalies and trends), data profiling, data algorithms, and (measure/develop) data maturity models and develop data strategy recommendations. 
• Explore large data sets for actionable information. Correlate similar data to find actionable results. Analyze large amounts of information to discover trends and patterns. 
• Build predictive models and machine-learning algorithms to increase and optimize user experiences, system capabilities and other business outcomes. Combine models through ensemble modeling. 
• Create reports and presentations for business uses. Present information using data visualization techniques. 
• Propose solutions and strategies to business challenges. Develop processes and tools to monitor and analyze model performance and data accuracy. Assess effectiveness and accuracy of new data sources and data gathering techniques.  
• Collaborate with engineering and product development teams, as well as peer data scientists both within eSimplicity and across the broader government agency. 
• Peer review analytics code and output. 
• Documenting, improving, and maintaining data strategies and artifacts including notebook and library code, logical and physical data models, data dictionary, data roadmap, and data security policies, using industry best practices and adhering to federal standards. 
• Providing subject matter expertise and leading data and architecture review meetings. 
• Reviewing and continuous improvement of data governance policies and processes. 

Requirements

Required Qualifications: 

• Minimum of 10 years applicable data science and/or data analysis experience. 
• A bachelor's degree in computer science, Information Systems, Engineering, Math, or other related scientific or technical discipline.  
• Extensive of experience in cloud data architecture (AWS preferred) and distributed big data technologies/tools, including Databricks, Spark, Redshift, and AWS Glue.,  
• Extensive experience querying databases and using SQL, Python, R, SAS, etc. 
• Experience with data analytical tools such as Databricks, AWS EMR Notebook/Studio, AWS Sagemaker, AWS QuickSight, and SAS/SAS Viya. 
• Understanding, planning for, and executing operations research. 
• Understanding of data management techniques and familiarity with data management tools. 
• Experience with data lake architectures and building ETL pipelines to ingest, process, and store data. 
• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests, and proper usage, etc.) and experience with applications. 
• Experience visualizing/presenting data for stakeholders using BI tools and open-source library packages from Python or R etc. 
• Experience in data mining. Knowledge and experience in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, etc. 
• Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, forecasting, etc. Understand the real-world advantages and drawbacks of each approach. 
• Experienced and knowledgeable analyzing and training models from sensitive data including advantages or disadvantages of various techniques. 
• Analytical and problem-solving skills; Analytical mind and business acumen. 
• Ability to visualize data in the most effective way possible for a given project or study 
• Ability to communicate complex data in a simple, actionable way, preferably incorporating the use of diagrams and pictures where appropriate.  
• Ability to work independently and with team members having different skill levels and from different backgrounds. 
• Excellent attention to detail. 
• Exceptional technical writing skills. 
• Strong math skills (e.g. statistics, algebra). 
• Individual and group problem-solving aptitude. 
• Excellent communication and presentation skills. 
• Flexible and willing to accept a change in priorities as necessary. 
• Ability to work in a fast-paced, team-oriented environment. 
• Experience with Agile methodology, using test-driven and prototyping development approaches. 
• Experience with Atlassian Jira/Confluence. 
• Experience using (AWS) cloud services and API’s. 
• Strong command of Microsoft Office products, particularly Excel. 
• Excellent command of written and spoken English. 
• Ability to obtain and maintain a Public Trust security clearance; residing in the United States. 

Desired Qualifications: 

• Graduate degree in Data Science or similar quantitative field. 
• Centers for Medicare and Medicaid Services (CMS) or Health Care Industry experience. 
• Experience with healthcare quality data including Medicaid and CHIP provider data, beneficiary data, claims data, and quality measure data. 
• Experience with data orchestration frameworks such as Apache Airflow and Luigi 
• Experience with MLOps CICD practices/tools and IaC tools such as Ansible, Terraform, and CloudFormation 

eSimplicity supports a remote work environment operating within the Eastern time zone so we can work with and respond to our government clients. Expected hours are 9:00 AM to 5:00 PM Eastern unless otherwise directed by your manager. 

Benefits: 

We offer a highly competitive salary, healthcare benefits and flexible leave policy. 

Equal Employment Opportunity: 

eSimplicity is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, gender, age, status as a protected veteran, sexual orientation, gender identity, or status as a qualified individual with a disability.