Data Scientist III - Veterans Health Administration

Qlarant is a not-for-profit corporation that partners with public and private sectors to create high quality, safe, and efficient delivery of health care and human services programs. We have multiple lines of business including population health, utilization review, managed care organization quality review, and quality assurance for programs serving individuals with developmental disabilities. Qlarant is also a national leader in fighting fraud, waste and abuse for large organizations across the country.  In addition, our Foundation provides grant opportunities to those with programs for under-served communities.

Qlarant has an exciting opportunity for experienced Data Scientists seeking to utilize their Veterans Health Administration (VHA) data experience.  Qualified applicants must have experience working with VHA data and live in the DC metro area.  This is not an immediate opening and is contingent upon contract approval.  While a home-based position, you must be able to travel to DC or other locations when required.  This is a full-time regular position that offers a collaborative and inclusive work environment, opportunities for advancement, excellent benefits, a generous leave program and a retirement plan that features an employer contribution equal to 10% of your annual earnings. 

The Data Scientist III is a mid-level professional position that applies innovative and big-data driven problem solving skills to predict the future based on past patterns.  This position designs experiments to solve sophisticated problems with code, and builds predictive models and machine learning algorithms. Identifies the questions that need to be asked and answered with data based on business problems, with the goal of helping the organization make better decisions.  The Data Scientist III possesses specialized experience in statistics and machine learning algorithms in addition to a strong business acumen and advanced coding and data visualization skills. 

 Essential Duties and Responsibilities include the following. Other duties may be assigned.

• Work directly with client stakeholders to understand and define analysis objectives and then translate these into actionable results.
• Develop a deep understanding of all the data relevant to the problem to be addressed. Utilize data wrangling capabilities to handle diverse and complex data at any scale to make analytics process more efficient and accurate.
• Establish deterministic and probabilistic linkages between structured and unstructured data sources and develop ways to extract and summarize the sought information in the data using a wide variety of statistical, data mining and machine learning techniques.
• Use machine learning and data mining techniques to understand the patterns in large volumes of data, identify relationships, correlate disparate datasets, detect data anomalies, and classify data sets.
• Design and build algorithms and predictive models using techniques such as linear and logistic regression, support vector machines, ensemble models (random forest and/or gradient boosted trees), neural networks, and clustering techniques.
• Converts designs and specifications into computer code. Compiles code into programs and corrects errors. Analyzes code to find causes of errors and revises programs.
• Create prototypes of productizable ways to perform the analysis at scale, provide documentation and help educate your colleagues.
• Validate and optimize model performance upon deployment and tracking over time as necessary.
• Present complex analysis results tailored to different audiences (e.g. technical, manager, executive) in a highly consumable and actionable form including the use of data visualizations.
• Work closely with client, product, and engineering teams to turn data into critical information and knowledge that can be used to make sound organizational and analytical decisions. Collaborate with these groups to incorporate Data Science capabilities into the organization’s products and services.
• Create opportunities to educate, train, convene, and support clients in how to best leverage data science.
• Assist leadership with strategies for scaling successful projects across the organization.
• Mentor lower level Data Scientists in all technical aspects of their work.
• Conduct causality experiments by applying A/B experiments or epidemiological approach to identify the root issues of an observed result.
• Validate and optimize model performance upon deployment and tracking over time as necessary.
• Present complex analysis results tailored to different audiences (e.g. technical, manager, executive) in a highly consumable and actionable form including the use of data visualizations.
• Work closely with client, product, and engineering teams to turn data into critical information and knowledge that can be used to make sound organizational and analytical decisions. Collaborate with these groups to incorporate Data Science capabilities into the organization’s products and services.
• Create opportunities to educate, train, convene, and support clients in how to best leverage data science.
• Assist leadership with strategies for scaling successful projects across the organization.
• Mentor lower level Data Scientists in all technical aspects of their work.

Supervisory Responsibilities

This job has no supervisory responsibilities.

To perform the job successfully, an individual should demonstrate the following competencies:

• Analytical - Synthesizes complex or diverse information; Collects and researches data; Uses intuition and experience to complement data.
• Problem Solving - Identifies and resolves problems in a timely manner; Gathers and analyzes information skillfully; Develops alternative solutions.
• Judgment - Exhibits sound and accurate judgment; Supports and explains reasoning for decisions. Design - Generates creative solutions; Translates concepts and information into images; Uses feedback to modify designs; Applies design principles; Demonstrates attention to detail.
• Language Skills
• Ability to read, analyze, and interpret common scientific and technical and professional journals, technical procedures, or governmental regulations.
• Ability to write reports, business correspondence, and procedure manuals.
• Ability to effectively present information and respond to questions from groups of managers, clients, customers, and the general public.
• Mathematical Skills
• Ability to work with multiple variables and constructs and hierarchical data structures.
• Ability to apply advanced mathematical concepts such as exponents, logarithms, quadratic equations, and permutations.
• Ability to perform mathematical and statistical computations and understand mathematical notation (e.g., be able to read a journal article describing a statistical techniques and then apply it to data).
• Reasoning Ability
• Ability to define problems, collect data, establish facts, and draw valid conclusions.
• Ability to interpret an extensive variety of technical instructions in mathematical or diagram form and deal with several abstract and concrete variables.
• Other Skills and Abilities
• Fluency in statistical programming and database software and MS Office.
• Ability to collaborate with business, engineering and product teams on cross-functional projects
• Ability to assemble, manipulate, and analyze data (including data extraction, cleaning, visualization, presentation, etc.)
• Ability to work with highly sensitive information while preserving the confidentiality of the information.
• Ability to deal with ambiguity in a fast-paced, dynamic environment.

• Master’s degree in quantitative field such as applied mathematics, statistics, biostatistics, physics, computer science, or operations research required.
• Minimum of four years work experience in a machine learning-focused role, including data extraction and cleaning, exploratory analysis, predictive modeling, monitoring of algorithms, coding and data visualization or a demonstrated equivalent combination of education and work experience in a relevant role.
• Verifiable work experience analyzing VHA data is required.
• Demonstrated understanding and ability to apply data analysis and machine learning across multiple domain areas.
• Demonstrated ability to create and analyze computer code in applicable programs.
• Demonstrated expertise with the latest statistical programming stack. Experience with programming languages such as Python, R, SAS, Matlab, SQL, Pig, Hive, and Scala strongly preferred.
• Proven experience developing creative solutions to challenging analytical problems.

Qlarant is an Equal Opportunity Employer of Minorities, Females, Protected Veterans, and Individuals with Disabilities.