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Information Technology 🏢 Full Time ⭐️ Verified

Senior Data Scientist

Nexus Analytics
San Francisco
Salary Estimate
USD 160.000 – USD 220.000
Live Update
15 Mei 2026
Deadline
15 Mei 2027

Job Description

Join Nexus Analytics as a Senior Data Scientist and transform complex data into strategic business intelligence. We're seeking an innovative thinker to leverage cutting-edge analytics and machine learning to drive data-driven decision-making across our global enterprise. This role offers the opportunity to work with Fortune 500 clients, solve high-impact challenges, and shape the future of data science in a dynamic, collaborative environment.

Responsibilities

  • Develop and deploy advanced predictive models using Python, R, and SQL to uncover actionable business insights
  • Lead end-to-end data science projects from hypothesis testing to production implementation
  • Collaborate with cross-functional teams to define data requirements and deliver scalable solutions
  • Design and optimize data pipelines ensuring data integrity and processing efficiency
  • Create compelling data visualizations and executive dashboards using Tableau/Power BI
  • mentor junior data scientists and contribute to innovation in our AI/ML practices
  • Translate complex findings into strategic recommendations for C-level stakeholders

Qualifications

  • Master's degree in Data Science, Statistics, Computer Science, or related field (Ph.D. preferred)
  • 5+ years of professional experience in data science or analytics
  • Expert proficiency in Python (Pandas, Scikit-learn, TensorFlow) and SQL
  • Proven track record of deploying ML models in production environments
  • Strong statistical analysis and experimental design capabilities
  • Experience with cloud platforms (AWS/GCP/Azure) and big data technologies
  • Exceptional communication skills with ability to articulate technical concepts to non-technical audiences

Required Skills

Python SQL Machine Learning TensorFlow Data Visualization Statistical Analysis AWS Data Engineering Predictive Modeling

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