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Analyze clinician platform data to identify behavioral patterns, develop product and client-facing analytics, and communicate actionable insights. The role collaborates with product managers, analysts, engineers, and other data scientists on projects spanning data ingestion, analysis, and recommendations. Responsibilities also include contributing to data team strategy and applying statistical methods, SQL, Python data libraries, visualization, and distributed data processing techniques.

Create client-facing analyses and reusable data products for Product, Analytics, Client Success, and Sales teams. Analyze large healthcare datasets to identify behavioral patterns among medical professionals, automate code, and communicate insights to technical and non-technical stakeholders. The role combines SQL, Python-based exploratory data analysis, data visualization, stakeholder collaboration, and opportunities to grow into presentation-focused or advanced technical work.

Plan and execute medical advisory summits, trade shows, corporate events, physician gatherings, webinars, and product demonstrations. Manage event calendars, budgets, vendors, logistics, invitations, programming, staffing, and on-site execution. Partner with senior leaders, physicians, speakers, and vendors while measuring attendance, engagement, and outcomes to improve future events.

Lead statistical measurement and client intelligence initiatives using healthcare, prescription, and claims data. Develop performance benchmarks, evaluate program impact, apply statistical and machine learning methods, advise data scientists, support survey-based measurement, manage analytics vendors, mentor analysts, and present findings to marketing teams and clients. The role requires advanced SQL and Python, healthcare data expertise, vendor management, and extensive quantitative experience.

Commercial Data Scientist will develop machine learning models, analyze large healthcare datasets, identify clinician behavioral patterns, and create reusable data products. The role partners with Product, Data, Strategy, Insights, and Sales teams to deliver client-facing analyses and data-driven recommendations. Responsibilities include statistical analysis, production model development, complex SQL querying, scalable data processing, automation, and communicating technical insights through compelling visualizations and narratives.

Prospect hospitals, health systems, and medical groups through phone, email, and social channels. Research accounts, identify decision-makers, qualify inbound and outbound opportunities, schedule discovery calls and demos, and document activity in Salesforce. Partner with sales teams on territory and expansion strategies, communicate Hospital Solutions’ value, manage funnel metrics, and consistently meet or exceed meeting and pipeline quotas.

Prospect for new and existing healthcare-related accounts through phone, email, and social media. Research territories, identify decision-makers, manage account and contact activity, achieve sales quotas, and collaborate with Business Development teams. The role also requires developing expertise in Doximity Talent Solutions and provides a pathway to a full-cycle Business Development position.

Serve as embedded legal counsel to AI and R&D teams, advising on product design, health data use, AI risks, regulatory requirements, and product launches. Draft and negotiate data, model, research, clinical, BAA, DPA, and pilot agreements. Build scalable legal processes, playbooks, and training while partnering with privacy, security, regulatory, clinical, trust and safety, and marketing teams.

Manage pharmaceutical client accounts from project kickoff through campaign completion, ensuring contract fulfillment, timeline management, content development, campaign measurement, client communication, and revenue recognition. The role requires coordinating internal and external teams, managing multiple projects independently, forecasting deliverables, and maintaining strong client relationships in a healthcare communications environment.

Design and build maintainable data pipelines, ETL processes, and data architecture standards. Collaborate with product managers, analysts, and machine learning engineers to translate requirements into automated, scalable solutions. Apply software engineering best practices, asynchronous systems, APIs, streaming, testing, monitoring, and Python and SQL expertise. Help prioritize data initiatives based on business impact and communicate complex technical concepts to technical and non-technical stakeholders.