Staff Data Scientist

Brahma Consulting Group

California (MO)

On-site

USD 140,000 - 210,000

Full time

4 days ago
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Job summary

Brahma Consulting Group seeks a Staff Data Scientist to lead enterprise-scale data initiatives focused on Master Data Management, record linkage, and entity resolution. You will unify siloed data into trusted data products and translate model outputs into actionable guidance for executives and clinical stakeholders.

Responsibilities include building predictive models, semantic data layers, and dashboards, mentoring junior analysts, and ensuring robust data governance and scalable pipelines for

Qualifications

  • 8+ years in data science, analytics, and data engineering.
  • Proven entity resolution and graph-based matching experience.
  • Production-grade Python and SQL coding.

Responsibilities

  • Entity Resolution & ML Modeling: Develop and deploy deterministic, probabilistic matching, and graph-based entity resolution models to solve large-scale record linkage challenges across enterprise data silos.
  • Analytics & Semantic Layer: Design data pipelines, establish metric frameworks, and build semantic layers to ensure high data quality, integrity, and robust validation.
  • Cross-Functional Collaboration: Partner with data governance, data engineering, and business teams to translate complex use cases into production-grade data science workflows and optimized pipelines.
  • Data Visualization & Storytelling: Build dashboards and visual frameworks to clearly communicate complex algorithmic outputs and model insights to non-technical stakeholders and executive leadership.
  • Technical Leadership: Provide technical guidance and mentorship to junior analysts, enforcing software development and data pipeline best practices.

Skills

8+ years experience
Entity resolution
Python & SQL

Education

Bachelor's/Master's/PhD in DS/CS/Statistics

Tools

Databricks
AWS (Glue/Redshift)
Git/GitHub/Jira/Confluence

Job description

We are seeking a Staff Data Scientist to lead high-impact data initiatives centered on Master Data Management, record linkage, and entity resolution across large, complex enterprise datasets. In this role, you will act as the primary domain expert for unifying siloed data into highly trusted, well-governed data products. You will work cross-functionally to design predictive models, build semantic data layers, and translate complex probabilistic outputs into clear, actionable logic for executive leadership and clinical stakeholders.

Key Responsibilities
  • Entity Resolution & ML Modeling: Develop and deploy deterministic, probabilistic matching, and graph-based entity resolution models to solve large-scale record linkage challenges across enterprise data silos.
  • Analytics & Semantic Layer: Design data pipelines, establish metric frameworks, and build semantic layers to ensure high data quality, integrity, and robust validation.
  • Cross-Functional Collaboration: Partner with data governance, data engineering, and business teams to translate complex use cases into production-grade data science workflows and optimized pipelines.
  • Data Visualization & Storytelling: Build dashboards and visual frameworks to clearly communicate complex algorithmic outputs and model insights to non-technical stakeholders and executive leadership.
  • Technical Leadership: Provide technical guidance and mentorship to junior analysts, enforcing software development and data pipeline best practices.
Qualifications & Skills
  • Experience: 8+ years of hands-on experience in data science, advanced analytics, and data engineering.
  • Entity Resolution Expertise: Proven track record with record linkage, deterministic/probabilistic matching models, and graph-based entity resolution at enterprise scale.
  • Technical Proficiency: Expert-level Python and SQL skills for writing production-grade, modular code. Experience with root-cause analysis on training/test samples to resolve model anomalies.
Data Stack & Tools:
  • Data Warehousing & Cloud: Databricks, AWS (Glue, Redshift).
  • Workflow: Git, GitHub, Jira, Confluence.
Education:

Bachelor’s, Master’s, or Ph.D. in Data Science, Statistics, Computer Science, or a related field.

Communication:

Exceptional ability to distill complex analytical findings into actionable business insights.

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