Consultant - Decision Analytics - Healthcare (5-8 yrs)

Job Description

Decision Analytics Consultants serve on project teams that deliver high-quality projects to clients. In particular, Consultants combine best-in-class analytic skills with strong problem-solving and communication abilities to lead analytical work to help clients solve strategic, tactical, and operational business problems. Consultants may work on multiple projects simultaneously. As Consultants advance in their career, they often specialize in a particular industry, practice area and/or client relationship

Responsibilities

- Work with project leadership to define project scope and develop approach

- Design and execute qualitative or quantitative analyses to help clients improve their commercial effectiveness

- Hands-on experience working on RWD based Observational studies to generate data evidence including but not limited to clinical, payer contracting, epidemiological use-cases

- Experience of Literature review - ability to execute systematic, quick and relevant literature review and to formulate POV on analytical techniques & methodology implemented

- Ability to contribute to the write-up and review of the study and/or model description, including relevant portions of protocols, manuscripts, abstracts, posters, slide presentations, as needed

- Lead project task execution by ensuring progress, organizing project data and coordinating team meetings

- Synthesize findings, develop recommendations and communicate results to clients and internal teams

- Program solving and insights generation -should be of quantitative mindset to understand client requirements, should be able to formulate data-driven approach for solving business problem, break down the approach into small logical components, conduct analysis, infer insights and storyboard the results

- Ability to guide the team-members and work closely with them to define and achieve the daily milestones

- Need to have strong sense of time urgency and the ability to handle and deliver with tight project timelines as needed

- Client communication and client management - should be able to lead meaningful discussions with the client and develop deep understanding of the nature of work to share new ideas and opportunity segments

- Provide thought leadership and innovation within projects and practice areas

- Contribute to internal firm activities

Qualifications

- MBA with a bachelor's (and often graduate) degree in a quantitative, analytical discipline, such as Operations Research, Applied Mathematics, Management Science, Data Science, Statistics, Econometrics, or Engineering. Alternately, candidates may possess a PhD in marketing, economics, decision sciences or related field with a business application. In lieu of an MBA or PhD, 5-8 years of relevant work experience may substitute

- 4 - 8 years' work experience with domain knowledge/expertise in Healthcare/Life Sciences/Med

Tech is preferred

- Relevant work experience, with evidence of strong analytic work (including use of advanced modeling techniques and tools such as R, SAS, Tableau, or VBA. Proficiency in hands on programing in SQL and advanced SQL, MS Excel. Hands on experience in either R/Python

- Working knowledge of basic Statistics including first order descriptive statistics, types of distributions, hypothesis testing, statistical significance, probability distributions etc.

- Good to have experience of bio-statistical techniques such as - Survival analysis, Matching techniques such as Propensity score Matching and Case Control, Linear and Logistic regression

- Fundamental understanding of standard predictive and classification models; when to use and how to interpret results

- Agile project planning and project management skills

- Analytical & problem-solving skills, with a creative and innovative outlook

- High motivation, good work ethic, maturity and personal initiative

- Aptitude for, and enjoyment of, leading and managing teams

- Strong oral and written communication skills that enable personal impact with senior-level decision makers

- Strong attention to detail, with a quality-focused mindset

- Client service orientation