Analytica is seeking a Data Scientist to perform in-depth evaluation and analysis of potential fraud cases and requests for information using claims information and other sources of data. The Data Scientist utilizes SAS, R, or Python to support the development of complex cases that involve high dollar amounts, sensitive issues, or that otherwise meet criteria for referral to law enforcement, recoupment of overpayment, and/or administrative action based on reactive and proactive data analysis.
Primary Responsibilities Include (But Are Not Necessarily Limited To):
Required skills, abilities, and certifications:
- Provide regulatory and compliance analysis, implementation, data analysis, and evaluation to identify potential fraud.
- Works with local management, investigators, and analysts to provide reactive and proactive case development support and to fulfill law enforcement data requests.
- Analyzes data to identify and compare norms, trends, and patterns
- Applies tools to detect potential fraud and support fraud investigations, organizing case files, research violations and accurately and document all steps taken in project development
- Maintains chain of custody on documents and follow all confidentiality and security guidelines.
- Validates data analysis results and analytically identifies potential fraud, waste and/or abuse situations in violation of Medicare/Medicaid laws, guidelines, policies, and regulations.
- Conducts self-directed research to uncover problems and provides data analysis support to the fraud investigation team in support of their investigation leads
- Supports management requests for CMS reporting requirements.
- Develops quality leads so that new case development can occur to meet contract requirements to identify new problems proactively
- Utilizes data analysis techniques to detect aberrancies in Medicare/Medicaid claims data and proactively seeks out and develops leads and cases received from a variety of sources including CMS and OIG, fraud alerts, and referrals from government and private sources.
- Works with Statisticians and Sr. Data Analysts to provide proactive data analysis results with statistically high probabilities of producing case referrals to law enforcement, overpayments, and/or administrative actions
- Responds in a timely and complete manner to data requests from internal and external customers
- Prepares, develops and participates in provider, beneficiary, law enforcement, or staff training as related to Medicare fraud, waste and/or abuse data analysis.so that contract requirements are met for case development access to data and innovative approaches to fraud
- Bachelor degree in statistics or related discipline with preference given to candidates with relevant work experience in healthcare claims analysis
- Have high proficiency level with MS Access and MS Excel.
- Requires 5+ years professional experience working with SAS, R, or Python to perform various types of data analysis.
- Knowledge of Medicare and Medicaid rules and regulation is a plus
- Demonstrated knowledge of various database management systems in order to input, extract or manipulate information.
- Demonstrated experience and knowledge of health care information (health claims data specifically Medicare and Medicaid , ICD-9-CM codes, physician specialty codes, pharmaceutical data including NCPDP file formats and codes, provider identifiers, etc) is preferred.
About ANALYTICA: Analytica is a leading consulting and information technology solutions provider to public sector organizations supporting health, civilian, and national security missions. Founded in 2009 and headquartered in Washington D.C., the company is an established SBA certified HUBZone and 8(a) small business that has been recognized by Inc. Magazine each of the past three years as one of the 250 fastest-growing companies in the U.S. Analytica specializes in providing software and systems engineering, information management, analytics & visualization, agile project management, and management consulting services. The company is appraised by the Software Engineering Institute (SEI) at CMMI® Maturity Level 3 and is an ISO 9001:2008 certified provider.
- Demonstrated knowledge in Machine Learning and AI with techniques such as: machine learning and decision trees
- Worked with data visualization tools such as:ggplot, d3.js and Matplottlib, and Tableau
- Exposure to working with unstructured data that may include videos, blog posts, customer reviews, social media posts, video feeds, audio etc.
- Ability to write technical documents that can describes handling and functionality of various data architectures and solutions.