Infosys LTD logo

Data Science Consultant 2

Infosys LTD

  • Tempe, AZ
  • 20 days ago

    Highlights

    Leverage tools like SAS and R/Python to create reusable customizations for non-ML, ML, and deep learning algorithms, while enhancing analytics including LLMs, and create innovative, cost-effective solutions. Develop models for complex use cases (e.g., forecasting models, LLM-based solutions), while refining algorithms to meet business needs, and ensure smooth deployment into scalable, production-ready solutions.
    Infosys LTD

    Numbers & Facts

    LocationTempe, AZ
    IndustryComputer/IT Services
    Company Size10,000 employees or more
    Websitehttps://www.infosys.com/careers

    Description

    Job Description

    In the assigned Job Role of Data Science Consultant 2, your Area Of Responsibility will be as below:

    • Develop data preparation tasks, while identifying patterns or anomalies.
    • Ensure data readiness for advanced modeling.
    • Develop models for complex use cases (e.g., forecasting models, LLM-based solutions), while refining algorithms to meet business needs, and ensure smooth deployment into scalable, production-ready solutions.
    • Conduct testing and optimize algorithms for performance, reliability, and scalability, while providing guidance to team members in best practices.
    • Design and develop predictive models and data-driven analyses to address business challenges.
    • Build, evaluate, and deploy models, standardize code, and contribute to knowledge management.
    • Leverage tools like SAS and R/Python to create reusable customizations for non-ML, ML, and deep learning algorithms, while enhancing analytics including LLMs, and create innovative, cost-effective solutions.
    • Define analytics problems for projects; execute visualization, analysis, and predictive modeling under guidance.
    • Proactively maintain models and implement improvements for accuracy and reliability.
    • Apply governance controls to mitigate risks and ensure compliance.
    • Analyze performance trends, recommend improvements, and document discrepancies for escalation.
    • Maintain comprehensive documentation standards, while participating in knowledge transfer sessions.
    • Participate in discussions with stakeholders to refine requirements, provide insights, and guide implementation of models.
    • Apply the predefined quality measurement framework at an individual task level in the project.
    • Deploy complex analytics tools or multi-system integration, while validating deployment success.
    • Participate in developing scripts or templates for repeated deployments tasks.
    • Contribute to analytic solutions, IP asset creation, and training initiatives.
    • Contribute to thought leadership such as papers, innovative non-ML, ML, deep learning or LLM models, and proofs of concepts.
    • Participate in and deliver analytics training, while contributing to content creation.
    • Provide input for segment and unit-level business plans.

    Your contribution to the team:

    • Deliver scalable, high-quality analytics solutions aligned to business needs.
    • A knack for optimization, deployment and performance improvement of models.
    • The ability to drive innovation through advanced analytics, automation and thought leadership.
    • Enable team growth through knowledge sharing, training and standardization.
    • Support business planning with data-driven insights.

    About Company

    Infosys is a global leader in next-generation digital services and consulting. We enable clients in 45 countries to navigate their digital transformation.

    With over three decades of experience in managing the systems and workings of global enterprises, we expertly steer our clients through their digital journey. We do it by enabling the enterprise with an AI-powered core that helps prioritize the execution of change. We also empower the business with agile digital at scale to deliver unprecedented levels of performance and customer delight. Our always-on learning agenda drives their continuous improvement through building and transferring digital skills, expertise, and ideas from our innovation ecosystem.

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