Data Scientist

Prime Talent Recruiting

  • Irvine, California
  • 1 day ago

    Highlights

    Over 5 years of experience designing, building, and deploying large-scale ML systems, with a preference for expertise in recommender systems, predictive modeling, or ad-tech. Experience with ML Ops on cloud platforms such as AWS, including container tools like Docker and Kubernetes, and workflow tools like Airflow and Kubeflow.

    Numbers & Facts

    LocationIrvine, California
    Websitehttps://primetalentrecruiting.com/

    Description

    Data Scientist - User Insights

    Salary $150k -$180k

    Position : Orange County - Hybrid

    Were looking for a Data Scientist to develop and deploy machine learning models that drive personalization and recommendation insights across SaaS and mobile app platforms.Candidate must be experienced in applying machine learning to real-world problems beyond just theoretical and mathematical concepts

    • Over 5 years of experience designing, building, and deploying large-scale ML systems, with a preference for expertise in recommender systems, predictive modeling, or ad-tech.

    • Proven track record of successfully bringing machine learning solutions to market.

    • You need to deliver data in a way that engineers can easily use and integrate into their systems

    What youll do:

    • Design, train, and deploy scoring and recommendation models that connect users with relevant offers and personalized experiences in an application.

    • Practical experience working with Generative AI and large language model workflows.

    • Collaborate with engineering, product teams to develop scalable machine learning systems that align with product goals .

    • Successfully moved several machine learning models from prototype to production, delivering real business results.

    • Skilled in Python and its tools like Pandas, PyTorch and TensorFlow.

    • Strong SQL knowledge and experience working with big data platforms like Spark and Snowflake.

    • Experience working hands-on with Generative AI and large language model workflows, including prompt engineering and fine tuning.

    • Experience with ML Ops on cloud platforms such as AWS, including container tools like Docker and Kubernetes, and workflow tools like Airflow and Kubeflow.

    • Experienced in integrating model services with scalable, version-controlled APIs for reliable deployment and maintenance.

    Perks:

    Medical, dental, and vision

    Wellness reimbursements 

    Unlimited PTO

    Equity opportunity

    401(k)



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