Analyst/Senior Analyst- Advanced Analytics

PharmaACE is a growing Global Healthcare Consulting Firm, headquartered in Princeton, New Jersey. Our expert teams of Business Analysts, based across the US, Canada, Europe, and India, provide Analytics and Business Solutions using our worldwide delivery models for a wide range of clients. Our clients include established, multinational BioPharma leaders and innovators, as well as entrepreneurial firms on the cutting edge of science. We have deep expertise in Forecasting, BusinessAnalytics, Competitive Intelligence, Sales Analytics, and the Analytics Centerof Excellence Model. Our wealthof therapeutic area experience cuts across Oncology, Immuno- science, CNS, CV-Met, and Rare Diseases. We support our clients' needs in Primary Care, Specialty Care, and Hospital business units, and we have managed portfolios in the Biologics space, Branded Pharmaceuticals, Generics, APIs, Diagnostics, and Packaging & Delivery Systems.

Brief Introduction:

If you are keen to work on analytical problem solving, then work in the area of advance data analytics/sciences to provide consulting to pharmaceutical clients.

As an Analyst/Sr. Analyst, you are expected to the manage onshore / client communication and mentor a team of analysts.

Advance data analytics/sciences Analyst/Sr. Analyst designs and implements analyses on patient level data or similar datasets.

Responsibilities:

• Analyze different pharmaceutical / life sciences data sets like claims data, electronic medical records, anonymous patient level data, prescription data & sales data, promotional data
• Communicate results to clients and team members
• Develop client relationships and serve as a key point of contact for the project
• Understanding business objectives and developing models that help to achieve them, along with metrics to track their progress
• Analyzing the AI/ML algorithms that could be used to solve a given problem and ranking them by their success probability
• Exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world
• Verifying data quality, and/or ensuring it via data cleaning
• Supervising the data acquisition process if more data is needed.
• Defining validation strategies and data augmentation pipelines
• Defining the preprocessing or feature engineering to be done on a given dataset
• Training models and tuning their hyperparameters
• Analyzing the errors of the model and designing strategies to overcome them
• Knowledge on Deep learning techniques is added advantage
• Deploying models to production
• Interpreting and analyzing both qualitative and quantitative data points; hypothesis building with Strong excel and PPT skills
• Process automation using SQL/Python/Other available technologies/ETL Tools etc.

Leadership:

• Foster learning mindset in the team to proactively develop research and story-telling skills, leveraging multiple sources of data to answer business questions.
• Develop new capabilities leveraging new sources of data and methods that include segment-level analysis, etc.
• Engage with internal and external stakeholders to build effective relationships to create win- win engagement models.
• Mentor/Guide team members who can benefit from your expertise and experience.

Qualifications:

• Bachelor’s or Master’s in Engineering
• 1-5 years of pharma / life science consulting job experience
• High motivation, good work ethic, maturity, and personal initiative
• Strong oral and written communication skills
• Strong excel and PowerPoint skills
• Adherence to client specific data privacy and compliance policies
• Knowledge on various commonly used transactional data assets and others including Volumes/ Value, Rx, Specialty level, Longitudinal Patient level data assets

Other Competencies:

• Entrepreneurial orientation.
• Excellent interpersonal and communication skills(written and verbal).
• Innovative and collaborative behavior, team player.
• Customer centricity and paying attention to details.