Lead Data Scientist
AI summary of the role
Lead Data Scientist on the RXA Data Science team, leading end-to-end data science projects from scoping to deployment for marketing and business decisions.
What you’ll do
- Lead design, development, and deployment of ML models and analytics
- Guide production model pipelines with Databricks and Azure ML
- Translate client goals into modeling strategies and deliverables
- Monitor and improve model performance
What you’ll bring
- 5-7 years in data science, analytics, or predictive modeling
- Lead sophisticated data science initiatives with technical strategy
- Strong Python, R, or SAS; advanced SQL; cloud (Azure/AWS)
- Expertise in regression, classification, clustering, A/B testing
Technologies
Databricks · Azure ML · Snowflake · Python · R · SAS · SQL · Tableau · Power BI
About OneMagnify
Integrated AI-powered marketing, data analytics, and digital experience platform for Fortune 1000 enterprises seeking measurable business outcomes.
Private Late · 500–1000 people
Source and classification
Internal deployment & tooling · Evidence for this classification:
problems into analytically sound solutions while ensuring technical excellence, timely delivery, and cross-functional collaboration. The Lead Data Scientist is responsible for leading the execution of end-to-end data science projects, from scoping and modeling to operationalization and insight delivery. You will partner with clients, internal teams, and technical stakeholders to develop and deploy scalable solutions that drive measurable business value. What you'll do: Lead the design, development, and deployment of statistical models, machine learning algorithms, and custom analytics solutions Collaborate consistently with team members to understand the purpose, focus, and objectives of each data analysis project, ensuring alignment and meaningful support Translate client goals into clear modeling strategies, project plans, and deliverables Guide the development of
More from the job description
OneMagnify is an AI native, platform-enabled B2B digital agency operating at the intersection of data, technology, and creativity. We help complex organizations drive measurable business outcomes by building smarter customer experiences and delivering highly integrated solutions across digital, media, and technology. By combining deep industry expertise with advanced analytics and artificial intelligence, we enable our clients to make better decisions, move faster, and compete more effectively in dynamic markets. You’ll be joining our RXA Data Science team, a group dedicated to leveraging advanced analytics, predictive modeling, and machine learning to drive smarter marketing and business decisions. As Lead Data Scientist, you will play a critical role in delivering impactful, data-driven solutions. In this role, you will bridge strategy and execution—translating complex business problems into analytically sound solutions while ensuring technical excellence, timely delivery, and cross-functional collaboration. The Lead Data Scientist is responsible for leading the execution of end-to-end data science projects, from scoping and modeling to operationalization and insight delivery. You will partner with clients, internal teams, and technical stakeholders to develop and deploy scalable solutions that drive measurable business value. What you'll do: Lead the design, development, [... source excerpt omitted ...] ns Collaborate consistently with team members to understand the purpose, focus, and objectives of each data analysis project, ensuring alignment and meaningful support Translate client goals into clear modeling strategies, project plans, and deliverables Guide the development of production-level model pipelines using tools such as Databricks and Azure ML Collaborate with engineering, marketing, and strategic partners to integrate models into real-world applications Monitor and improve model performance, ensuring high standards for reliability and business relevance Present complex analytical results to technical and non-technical audiences in a clear, actionable format S
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