Lead Analyst, Commercial Data & AI
New
J
JobgetherOrthopaedics
Fully remote position within the United StatesFull-TimeLead
Salary94,000 - 151,800 USD per year
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Job Details
- Experience
- At least 5 years of experience
- Required Skills
- SQLSnowflakeGenerative AICRM
Requirements
- At least 5 years of experience in analytics, data science, marketing analytics, or customer analytics.
- Hands-on experience with CRM and lifecycle measurement.
- Advanced SQL proficiency, including complex joins, common table expressions (CTEs), and window functions.
- Ability to work with large, complex datasets.
- Hands-on experience with Alteryx Designer developing, automating, and optimizing end-to-end data workflows.
- Strong data cleaning, blending, transformation, and integration capabilities across multiple sources.
- Knowledge of orthopaedics products, clinical procedures, and relevant customer profiles.
- Ability to translate business needs into analytical hypotheses, methodologies, recommendations, and effective data structures.
- Knowledge of CRM data privacy principles, including consent management, suppression rules, PII, and data governance controls.
- Preferred experience with CRM or commercial platforms such as Salesforce Life Sciences Cloud, Marketing Cloud, Movemedical, or Tableau Server.
- Preferred familiarity with cloud data platforms and warehouses, including Reltio, AWS, Snowflake, SAP, Amazon Redshift, or Databricks.
- Preferred experience with generative AI, prompt engineering, RAG, model evaluation, and AI safeguards.
Responsibilities
- Build and maintain trusted customer data assets, source-of-truth datasets, and standardized definitions.
- Document analytical logic and ensure workflows are reproducible.
- Monitor and improve data accuracy, completeness, and consistency across commercial systems and data sources.
- Develop KPI frameworks and data models, and deliver insights supporting lead generation, opportunity management, customer engagement, and commercial execution.
- Prototype, test, and evaluate generative AI applications with safeguards, human validation, and performance measurement.
- Partner with Marketing, Sales, Product, and Data Strategy teams to structure business questions and deliver recommendations.
- Apply privacy, consent management, security, and AI governance requirements while addressing bias and fairness risks.
- Coach analysts on analytical rigor, SQL, experimentation, data quality, governance, and reproducible workflows.
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