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CDnA - Data Platforms Manager - Rare Diseases
Job Description
In this vital role you will be responsible for oversight, governance, and administration of our client’s US commercial data & analytics warehouse, lead cross-functional data & analytics enablement efforts and work on data science models. This role will report to the Senior Manager of Data Sciences and will be part of a cross-functional data governance team to ensure timely and accurate data for business analysis and decision making.
Responsibilities:
Qualifications:
Preferred Qualifications:
Responsibilities:
- Lead the US commercial Data Lake as a business owner for one or more therapeutic areas (TAs)
- Enable and participate in product launches by Onboarding and setting up new sources and data sets for Analytics; Reporting, etc.
- Lead new capabilities of the Data Platforms, including but not limited to, requests that have an impact on multiple domains in pharma (ex. Medical, commercial, compliance, etc.)
- Product Owner for Data Requests from multiple collaborators - including Secondary Analytics teams, Data Sciences and Forecasting, etc.
- Responsible for the management of both identified as well as de-identified patient data sets
- Business Owner and SME for the Assigned Therapeutic Areas
- Lead POCs and Tech evaluations in partnership with the IS team
- Lead efforts to optimize the Data ecosystem and better support customers
- Lead implementation of data solutions in support of all partners
- Lead and support cross-functional prioritization of data platform requests in co-ordination with Leads from Commercial Sales, Marketing, and Web
- Crafting prototypes and demos to better access and use data assets
- Be an integral part on projects and/or programs with strive to systematically derive insights that drive substantial business value for the company and its patients
- Identifying business needs and proposing potential data science solutions
- Communicating analysis ideas, progress and results to leadership and business partners
- Ensuring systems and models meet business requirements and industry standards
- Assuring compliance with regulatory, security, and privacy requirements as it relates to data assets
- Ad hoc projects and analysis would be a standing 10-20% of the role
Qualifications:
- Doctorate degree
- Or Master’s degree and 2 years of data science, business, statistics, data mining, applied mathematics, business analytics, engineering, computer science or commercial operations experience
- Or Bachelor’s degree and 4 years of data science, business, statistics, data mining, applied mathematics, business analytics, engineering, computer science or commercial operations experience
- Or Associate’s degree and 8 years of data science, business, statistics, data mining, applied mathematics, business analytics, engineering, computer science or commercial operations experience
- Or High school diploma / GED and 10 years of data science, business, statistics, data mining, applied mathematics, business analytics, engineering, computer science or commercial operations experience
Preferred Qualifications:
- Biotech and/or pharmaceutical industry experience
- MS in Engineering, Computer Science, Mathematics, Data Sciences, Statistics, or Operations
- 3+ years of relevant work experience in commercial operations
- Motivated teammate with demonstrated in problem-solving, data, analytics, and operations
- Experience with pharmaceutical data sets such as patient-level data sets, sales data sets(XPO, DDD, chargebacks, vendor data), and claims datasets (SHS, IQVIA), publications, KOLs, and Medical activity data, etc.
- Ability to direct and lead work through others (e.g. cross-functional partnership and/or vendor)
- Technical proficiency with strong logical, problem solving, and decision-making skills
- Experience with Agile Methodology of implementation of projects
- Experience with working with cross-functional teams in prioritizing tasks
- Cross-functional and leadership negotiating and influencing skills
- Training and presentations skills from prior experience
- Excellent organization/planning skills and talent for managing many large and complex datasets
- Ability to collaborate, partner and influence leadership/business partners and other IS resources to drive analytic projects end-to-end
- Ability to communicate analysis in a clear, detailed, and impactful manner
- Passion for learning and staying on top of current developments in advanced analytics
- Hands-on data engineering, AI/ML modeling experience, prototyping and reporting (BI tools)
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