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Data Scientist - W2

Job in San Jose, Santa Clara County, California, 95199, USA
Listing for: Dataflix
Full Time position
Listed on 2026-01-12
Job specializations:
  • IT/Tech
    Data Scientist, Machine Learning/ ML Engineer, Data Analyst, AI Engineer
Salary/Wage Range or Industry Benchmark: 200000 - 250000 USD Yearly USD 200000.00 250000.00 YEAR
Job Description & How to Apply Below
Position: Data Scientist - Open on W2 only

Overview

We are seeking a highly motivated and detail-oriented Data Scientist to join our team. In this role, you will be responsible for analyzing large datasets to uncover insights, develop predictive models, and help guide strategic decisions across the organization. You’ll collaborate closely with business stakeholders, data engineers, and software developers to drive data-driven innovation and continuous improvement.

Key Responsibilities
  • Analyze structured and unstructured data using statistical, machine learning, and data mining techniques.
  • Build, validate, and deploy predictive and prescriptive models to solve business problems.
  • Communicate findings and insights clearly to both technical and non-technical stakeholders.
  • Design and implement experiments (A/B testing, multivariate testing) to evaluate new strategies or features.
  • Collaborate with engineering teams to deploy models and ensure scalable, real-time analytics.
  • Develop data visualizations, dashboards, and reports to monitor key metrics.
  • Stay up-to-date with industry trends, tools, and technologies in data science and machine learning.
Requirements
  • Advanced degree in Computer Science, Statistics, Math, or equivalent experience.
  • 8+ years in Data science and Machine Learning.
  • Proficiency in ML techniques, SQL, Python/R, and big data frameworks.
  • Strong SQL skills for data extraction and transformation.
  • Experience with AI agents, LLMs, and fraud detection tools.
  • Experience with data visualization tools (e.g., Tableau, Power BI, matplotlib, seaborn).
  • Familiarity with cloud platforms (e.g., AWS, GCP, Azure) and big data technologies (e.g., Spark, Hadoop) is a plus.
  • Solid understanding of statistics, machine learning algorithms, and experimental design.
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