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Senior Data Scientist

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Senior Data Scientist

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Senior Data Scientist

Skills

Google Cloud PlatformDeep LearningDockerPythonData ScienceNumPypandasPyTorchTensorFlowGitMachine LearningAIAWSKubernetesNLP / Natural Language ProcessingApache AirflowBusiness TransformationAzure

1 month ago

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Important information


Contract type:

Permanent

Location:

Telangana, India

Work mode:

Onsite

Published on:

22 September 2026

What they need


Job Title: Data Science

Experience Level: 7-11 Years

Location: Hyderabad

Budget - Upto 30 LPA

Job Summary

We’re looking for a Senior Data Scientist with strong analytical thinking, deep technical expertise, and a proven ability to apply machine learning to solve real-world problems. The candidate should have 4+ years of high-quality proven experience in AI/ML working. You’ll work with cross-functional teams to design, develop, and deploy scalable AI/ML solutions, including Generative AI, predictive modeling, and recommendation systems.

Key Responsibilities

  • Design, build, and validate machine learning and deep learning models, ensuring robustness, scalability, and explainability.
  • Apply strong statistical foundations to analyze large datasets and derive actionable insights.
  • Lead the development and evaluation of models using modern ML frameworks (e.g., scikit-learn, PyTorch, TensorFlow).
  • Drive the adoption of Generative AI and LLM-based solutions, ensuring model alignment, prompt engineering, and ethical AI practices.
  • Collaborate with data engineers, product teams, and business stakeholders to transform business problems into technical solutions.
  • Contribute to code reviews, model documentation, and mentorship of junior data scientists.
  • Stay abreast of the latest research and translate cutting-edge methods into production.

Required Qualifications

  • Bachelor’s or master’s degree in computer science, Statistics, Applied Mathematics, or a related field.
  • Statistical and Mathematical Rigor
    • Strong grasp of descriptive and inferential statistics (hypothesis testing, A/B testing, regression, probability theory).
    • Understanding of bias-variance trade-off, regularization, overfitting, and model validation techniques.
  • Machine Learning & Deep Learning
    • Hands-on experience with a range of algorithms: decision trees, ensemble models, SVMs, neural networks, clustering, and NLP techniques.
    • Proficiency in deep learning architectures such as CNNs, RNNs, Transformers, and LSTMs.
  • Generative AI & LLMs
    • Conceptual and practical knowledge of Large Language Models (e.g., GPT, BERT, LLaMA), fine-tuning, embeddings, and prompt engineering.
    • Familiarity with generative modeling approaches (e.g., VAEs, GANs, diffusion models) is a strong plus.
  • Programming & Problem Solving
    • Advanced proficiency in Python with the ability to write clean, modular, and testable code.
    • Experience with libraries such as NumPy, pandas, matplotlib, scikit-learn, PyTorch, TensorFlow, and HuggingFace.
    • Strong problem-solving skills with the ability to tackle coding challenges independently and efficiently.
  • Tooling & Deployment
    • Experience with cloud platforms (AWS, GCP, Azure), ML pipelines (MLflow, Airflow, Kubeflow), and containerization (Docker, Kubernetes).
    • Version control (Git) and collaborative development practices.

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