ConcertAI

Analytics Consultant

Job Description

Posted on: 
February 20, 2023

CAI is looking for an Analytics Associate within the Customer Success organization.  This Analytics Associate will support the Strategic Data Science team by aiding the implementation of CAI’s leading real-world data products and clinical cloud capabilities. You will be part of the team providing strategic guidance for our pharmaceutical and biotechnology partnership requests for real-world data (RWD) consultation, about RWD fueled platforms, and related to RWD analytic services to ensure that the right CAI experts are leveraged at the right time and that optimal value from CAI products are realized.

The successful candidate will have experience identifying the business questions, deriving insights from data, and effectively communicating the technical aspects and value of applying RWD to development programs and lifecycle management. The candidate will be expected to quickly develop a deep understanding of all CAI data products and technology platforms. This role reports to the Executive Director, Strategic Data Science for Customer Success.

Responsibilities

  • Support the broader Customer Success Strategic Data Sciences team in establishing and maintaining key partner stakeholder relationships at the largest pharmaceutical and biotechnology companies
  • Use/code in CAI data, technology, and analytics to support client activities, publications and/or regulatory submissions in an effort to advance their assets in the market
  • Answer client business requirements related to CAI data, technology, analytics, and outcomes studies in a fast-paced environment
  • Be the technical liaison between the client and CAI clinical, epidemiology, AI, statistical experts to answer requests
  • Create a ‘story’/presentation that effectively ties together Data Science analyses, and present it in a compelling value-demonstrating
  • Collaborate with business development and customer success to expand the account and to meet internal group metrics
  • Evangelize CAI capabilities to external stakeholders and support technology pre-sales and post-sales efforts in partnership with customer success, business development and product teams.
  • Identify barriers to partner implementation of CAI products and technologies, and work with internal and client stakeholders to develop implementation strategies and deploy and solutions.
  • Assist CAI business units with coordinating delivery schedules, manage client expectations, and assure successful integration of products and technology into partner workflows.

Job Requirements

  • Bachelors and/or Masters or equivalent in a quantitative field such as: computer science, AI/Machine Learning, data science, statistics, biostatistics, mathematics, epidemiology or in a related discipline
  • 3+ years’ experience in life Science or biotech industry in a Data Science role.
  • 3+ years’ experience in a client-facing role supporting real-world data (RWD) client projects would be a plus.
  • 2+ years of experience in (RWD) study design, data preparation, and data modeling
  • Strong programming skills in Python, R, SQL, SPSS and deep knowledge of RWD/transactional patient-level data sets and how best to select the right data sources given the study question at hand Excellent communication skills and ability to ‘translate’ between the data and the business, via layman’s terminology of complex analytical methods
  • Experience with Cloud-based platforms
  • Client facing experience
  • Proven experience working with large, individual-level data sets or in a (RWD) data analyst role
  • Excellent time management skills, contributing to multiple projects with competing timelines
  • Proven past success in high-growth, fast-paced, start-up companies
  • Comfortable with ambiguity/flexibility
  • Strong emotional intelligence
  • Good listener, strategic thinker, and a team player
  • Oncology experience is a plus
  • Prior management consulting experience is a plus
  • SaaS experience is a plus
  • Experience designing and executing prospective or retrospective database studies is a plus
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