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    Scientist - Pittsburgh, United States - TATA Consulting Services (USA)

    TATA Consulting Services (USA)
    TATA Consulting Services (USA) Pittsburgh, United States

    3 weeks ago

    Default job background
    Description

    Skill:
    Data Scientist


    Must have:

    • 5-7 years of experience in data manipulation, statistical modeling, and data analysis.
    • Strong problem-solving skills with a focus on product development.
    • Proficiency in statistical computer languages (e.g., R, Python (Preferrable)) for data manipulation and analysis.
    • Experience in data architecture design and implementation.
    • Comprehensive knowledge of machine learning techniques (e.g., clustering, decision tree learning, artificial neural networks) and their practical applications.
    • Familiarity with advanced statistical concepts (e.g., regression, distribution properties, statistical tests).
    • Exp in GEN AI in GCP/Azure, exposure to LLM, exp in LLM Prompts.
    • Excellent written and verbal communication skills for effective collaboration across teams.
    • A passion for exploring new technologies and techniques.

    Experience Required:

    • Coding knowledge and experience in multiple languages (Java, Python).
    • Expertise in statistical and data mining techniques (e.g., GLM/Regression, Random Forest, Boosting, Trees).
    • Experience querying databases and using statistical computer languages (e.g., R, Python).
    • Familiarity with web services/ APIs.
    • Experience developing and applying advanced machine learning algorithms (e.g., regression, simulation, modeling, clustering).
    • Experience analyzing data from third-party providers (e.g., Google Analytics, Site Catalyst).
    • Knowledge of distributed data/computing tools (e.g., Map/Reduce, Hadoop, Hive, Spark).
    • Experience working in a cloud platform Azure, GCP, AWS and their data warehouse technologies - BigQuery, Snyapse etc.

    Responsibilities:

    • Collaborate with stakeholders across the organization to identify opportunities for data-driven solutions.
    • Mine and analyze data from company databases to optimize processes and business strategies.
    • Evaluate the effectiveness and accuracy of new data sources and data gathering techniques.
    • Develop custom data models and algorithms to apply to datasets.
    • Utilize predictive modeling to enhance customer experiences, revenue generation, and other business outcomes.
    • Establish and implement an A/B testing framework to assess model quality.
    • Partner with functional teams to implement models and monitor their impact.
    • Develop processes and tools to monitor model performance and data accuracy.
    #LI-NR3
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