Senior Data Scientist

6 days ago

Pune, Maharashtra, India beBeeMachineLearning Full time ₹ 15,00,000 - ₹ 25,00,000
Job Title

We are seeking a skilled and innovative Machine Learning Engineer with over 5 years of experience to design, develop, and deploy scalable ML solutions.

You will work closely with data scientists, software engineers, and product teams to solve real-world problems using state-of-the-art machine learning and deep learning techniques.

  • Design, build, and optimize machine learning models and pipelines for classification, regression, clustering, recommendation, and forecasting
  • Implement and fine-tune deep learning models using frameworks like TensorFlow, PyTorch, or Keras
  • Collaborate with cross-functional teams to understand business problems and convert them into technical solutions
  • Develop data preprocessing, feature engineering, and model evaluation strategies
  • Build and deploy models into production using CI/CD practices and MLOps tools
  • Monitor model performance and retrain as necessary to ensure accuracy and reliability
  • Create and maintain technical documentation, and provide knowledge sharing within the team
  • Stay updated on the latest research, tools, and techniques in machine learning and AI
Required Skills & Qualifications

To succeed in this role, you should have:

  • 5+ years of experience in Machine Learning Engineering or Applied Data Science
  • Proficiency in Python and ML libraries such as scikit-learn, pandas, NumPy, TensorFlow, or PyTorch
  • Solid understanding of mathematics, statistics, and ML/DL algorithms
  • Experience with end-to-end ML lifecycle from data collection and cleaning to model deployment and monitoring
  • Strong knowledge of SQL and working with large datasets
  • Experience deploying ML models on cloud platforms (e.g., AWS, Azure, GCP)
  • Familiarity with Docker, Kubernetes, MLflow, or other MLOps tools
  • Good understanding of REST APIs, microservices, and backend integration
Bonus Points

The following skills will give you an extra edge:

  • Exposure to NLP, Computer Vision, or Generative AI techniques
  • Experience with big data technologies like Spark, Hadoop, or Hive
  • Working knowledge of data labeling, AutoML, or active learning
  • Experience with feature stores, model registries, or streaming data (Kafka, Flink)
Educational Background

A degree in one of the following fields is a must:

  • Computer Science
  • Data Science
  • Statistics
  • Applied Mathematics
  • A related field

Additonal certifications in AI/ML are a plus.

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