About DataZymes:

Founded in 2016, DataZymes is a next-generation analytics and data science company driving technology and digital-led innovation for our clients, thus helping them get more value from their data and analytics investments.

Our platforms are built on best-of-breed technologies, thus protecting current investments while providing clients more bang for their buck. As we are a premier partner for many Business Intelligence and Information Management companies, we also provide advisory and consulting services to clients helping them make the right decisions and put together a long-term roadmap.

Our mission at DataZymes is to scale analytics and enable healthcare organizations in achieving non-linear, long term and sustainable growth. In a short span, we have built a high-performance team in focused practice areas, built digital-enabled solutions and are working with some marquee names in the US healthcare industry.

Roles and Responsibilities:

·       Ensuring objectivity of brand/therapeutic area forecasts through establishing objectives aligned around forecast accuracy.

·       Developing brand volume forecasts, both short-term and long-term, to feed into strategic and operational planning processes.

·       Sensitivity analysis to assist in opportunity identification and risk management.

·       Undertake strategic long-term brand and franchise forecasting and provide strategic perspective/guidance on portfolio and brand strategy, as well as new product introduction volume forecasting and guidance.

·       Develop a deep understanding of customers' data and analytical needs focusing on the customer-facing model leadership.

·       Solve brand-level analytical problems using quantitative approaches.

·       Review sales performance, insights data, key initiatives, and new launches with brand and customer teams to ensure robust plans are in place and being executed.

·       Develop and maintain key collaborative relationships with internal cross functional and external partners to initiate and obtain relevant data and analysis for forecast inputs.

·       Confidently present and defend forecast approach, methodology, assumptions, and output at the executive level.

·       Recommend and lead initiatives dedicated to the advancement and implementation of new forecast approaches and methodology.

·       Provide increased focus on analytics and emphasize on providing valuable insights to drive improvement opportunities.

·       Monitor the external environment to stay up to date on leading analytic capabilities, both within and outside of pharma, which can be applied within the organization.

·       Experience in working with large datasets, derive insights and present information through visualization and reports.

Must Have Skills

·       5+ years of analytical experience, 3+ years of pharmaceutical forecasting experience. 

·       Experience in strategic forecasting and new product launch is required.

·       Good understanding of primary market research, advanced analytics, and competitive intelligence.

·       Strong technical experience in Time series modelling

·       Strong technical experience in MS Office – Must be an advanced user of PPT and Excel

·       Strong verbal and written communication skills

·       Ownership of tasks assigned without supervisory follow-up

Good to Have Skills

·       Experience in Python/R/SAS good to have

·       Capability in applying deeper technical skills and knowledge that is shared across the functional area (e.g., deep knowledge of key data sets, modeling capabilities, etc.).

·       Experience in standard datasets in the Pharmaceutical Industry e.g. IQVIA (MIDAS, DDD NPA, Xponent, etc), claims data (Truven, Marketscan), Epidemiological data etc

Strong interpersonal skills, with an ability to do client interactions.

Capitalizes on opportunities to pursue value. Brings issues out in open so that all concern can address and find solution.

Building professional relationships with members of the client team.

Has an open and learning mindset. Adapts to new learning approaches and methods.