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Lead Data Scientist @ Orange Business

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 Lead Data Scientist

Job Description

about the role
  • 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.

about you
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.



Job Classification

Industry: IT Services & Consulting
Functional Area / Department: Data Science & Analytics
Role Category: Data Science & Machine Learning
Role: Data Scientist
Employement Type: Full time

Contact Details:

Company: Orange Business
Location(s): Noida, Gurugram

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Keyskills:   Computer science GCP Neural networks Machine learning Conceptualization Data mining Monitoring Analytics SQL Python

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