Lead Data Scientist - Gurgaon / Gurugram - Orange Business Services

    Orange Business Services
    Orange Business Services Gurgaon / Gurugram

    1 week ago

    Full time ₹4,500,000 - ₹9,000,000 (INR) per year *
    Description
    • Design, develop, and deploy machine learning models that meet business needs and deliver measurable impact.
    • Manage the end-to-end lifecycle of AI/ML models, including data gathering, feature engineering, model training, testing, and deployment.
    • Collaborate with data engineers, product managers, and business stakeholders to understand project requirements and deliver impactful solutions.
    • Guide the development and optimization of large-scale data pipelines to support model training and deployment.
    • Develop, Implement, and enhance models in areas such as predictive analytics, GenAI, natural language processing (NLP), deep learning, and recommendation systems.
    • Ensure the scalability, efficiency, and accuracy of machine learning models in production environments.
    • Mentor and guide junior data scientists and ML engineers, fostering a culture of learning and innovation.
    • Stay up-to-date with the latest industry trends, technologies, and research in machine learning, AI, GenaI and data science, and apply relevant insights to projects.
    • Communicate technical concepts and results effectively to business stakeholders and senior leadership.
    • Work closely with DevOps and engineering teams to manage the lifecycle of ML models, including versioning, monitoring, and maintenance.
    • Contribute to the strategic direction of the AI/ML/GenaI practice within the organization.

    6+ years of experience in data science / machine learning, with at least 2 years as a Senior Data Scientist/ML Engineer with the following skills and tools/technologies:

    • Bachelor s/PG degree in Engineering, Computer Science, Data Science, Statistics or a related field with a focus on analytics skills.
    • Proven experience leading end-to-end machine learning projects, from conceptualization to deployment.
    • Strong knowledge of machine learning algorithms, model evaluation metrics, and best practices for model deployment.
    • Proficiency in Python used in data science and ML. Familiarity with big data technologies and cloud services.
    • Working knowledge of a variety of machine learning techniques and concepts (regression, time series, classification, Ensemble modeling, Gradient, Boosting, stacking, clustering, decision trees, Neural Networks, image/text processing/NLP, AI, XAI, Transformers/LLM/GenAI and RAG etc.)
    • Solid understanding of statistical analysis, data mining, and data visualization techniques.
    • Good to have experience with MLOps practices to ensure the smooth operation of models in production.
    • Hands-on experience with machine learning libraries (e.g., TensorFlow, PyTorch, Scikit-learn, pretrained ML models, Transformers, RAG ), and advanced SQL.
    • Ability to tackle complex problems, break them down into actionable steps, and deliver practical solutions.
    • Excellent verbal and written communication skills, with the ability to translate complex data insights into clear and actionable recommendations.
    • Understanding of how to align machine learning and AI solutions with business goals.
    • Ability to work cross-functionally with teams across engineering, product, and business domains.
    • Experience with cloud platforms, including Google Cloud Platform (GCP) , Azure for machine learning / GenAI.
    * This salary range is an estimation made by beBee
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