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    Job · 17963775

    PUNE · FULLTIME

    Lead Data Scientist - Classical ML

    Code Vyasa logo

    Code Vyasa

    Pune · onsite · Posted 35d ago

    Sourced fromNaukri
    ₹12.0L - ₹17.0L PA10–15 yrsfulltimePune

    About a minute. You'll make an account on the way through.

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    Section · 01

    About this role

    Location: Chennai / Coimbatore / Bangalore / Pune


    We are looking for an experienced Lead Data Scientist with strong expertise in Classical Machine Learning, Deep Learning, NLP, and data engineering technologies. The ideal candidate will be responsible for designing and deploying scalable ML solutions, leading data science initiatives, and working closely with engineering and business teams to translate complex business problems into data-driven solutions.


    Key Responsibilities

    • Lead the design, development, and deployment of machine learning models for business use cases.
    • Develop and optimize Classical ML models using XGBoost, LightGBM, Regression, Classification, and other relevant techniques.
    • Apply Deep Learning and NLP techniques to solve complex business problems.
    • Perform data exploration, feature engineering, model development, validation, and optimization.
    • Work with large datasets using Python and SQL.
    • Build and deploy ML solutions leveraging Azure services.
    • Work with Snowflake for data storage, processing, and analytics.
    • Monitor model performance and continuously improve model accuracy and scalability.
    • Collaborate with Data Engineers, ML Engineers, Product Managers, and business stakeholders.
    • Provide technical leadership, mentor junior data scientists, and drive best practices across the data science lifecycle.
    • Translate business requirements into practical, measurable ML solutions.

    Required Skills

    • 10+ years of experience in Data Science / Machine Learning.
    • Strong hands-on experience with Classical Machine Learning.
    • Expertise in:
      • XGBoost
      • LightGBM
      • Regression
      • Classification
      • Feature Engineering
      • Model Evaluation & Optimization
    • Good experience with Deep Learning and NLP.
    • Strong proficiency in Python and SQL.
    • Experience working with Azure cloud services.
    • Hands-on experience with Snowflake.
    • Strong understanding of ML algorithms, statistics, model validation, and data preprocessing.
    • Experience leading or mentoring Data Science teams/projects.

    Good to Have

    • Experience taking ML models from POC to production.
    • Exposure to MLOps / model deployment and monitoring.
    • Experience working with large-scale enterprise datasets.
    • Strong stakeholder management and communication skills.

    Candidate Profile

    • Strong problem-solving and analytical mindset.
    • Ability to independently own ML projects from requirement gathering through deployment.
    • Comfortable working in a fast-paced, collaborative environment.
    • Strong technical leadership and communication skills.

    Sourced from naukri

    Section · 02

    Skills

    Model DeploymentClassical Machine LearningregressionXgboostclassificationNatural Language Processingdata scientistfeature engineeringLightGBMPythonSQLDeep LearningSnowflakeMicrosoft AzureData ScienceMachine Learning

    Section · Company

    About Code Vyasa

    Code Vyasa logo

    Code Vyasa

    IT Services & Consulting

    501-1000

    employees

    2018

    8 years old

    Jacksonville, Florida

    United States

    ₹11.4L PA avg

    Avg at Code Vyasa

    ₹12L – ₹17L PA

    This role

    About

    CodeVyasa is a Software Product-Engineering and Development company that helps Early-stage & Mid-Market Product companies with IT Consulting, App Development, and On-demand Tech Resources. Our Journey over the last 3 years has been nothing short of a roller-coaster. Along our way, we've won some of the most prestigious awards while driving immense value to our customers & employees.

    Industries

    ConsultingInformation TechnologyProfessional Services

    Employee ratings

    10 reviews

    3.4/ 5

    Culture

    4.0

    Career growth

    4.0

    Work-life

    4.1

    Employees rate it well for

    Work-Life Balance35Overall Company34

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