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Data Scientist - Artificial Intelligence / Machine Learning

Data Scientist - Artificial Intelligence / Machine Learning

TheThreeAcrossGurugram
24 days ago
Job description

Position : Data Scientist.

Experience : Min 3 Years.

Work Mode : Remote.

Notice Period : Max.30 Days (45 for Notice Serving).

Interview Process : 2 Rounds.

Interview Mode : Virtual Face-to-Face.

Interview Timeline : 1 Week.

Industry : Must be from a BPO / KPO / Shared Services or Healthcare Org.

Key Responsibilities :

AI / ML Development & Research :

  • Design, develop, and deploy advanced machine learning and deep learning models to solve complex business problems.
  • Implement and optimize Large Language Models (LLMs) and Generative AI solutions for real-world applications.
  • Build agent-based AI systems with autonomous decision-making capabilities.
  • Conduct cutting-edge research on emerging AI technologies and explore their practical applications.
  • Perform model evaluation, validation, and continuous optimization to ensure high performance.

Cloud Infrastructure & Full-Stack Development :

  • Architect and implement scalable, cloud-native ML / AI solutions using AWS, Azure, or GCP.
  • Develop full-stack applications that seamlessly integrate AI models with modern web technologies.
  • Build and maintain robust ML pipelines using cloud services (e.g., SageMaker, ML Engine).
  • Implement CI / CD pipelines to streamline ML model deployment and monitoring processes.
  • Design and optimize cloud infrastructure to support high-performance computing workloads.

    • Data Engineering & Database Management :

  • Design and implement data pipelines to enable large-scale data processing and real-time analytics.
  • Work with both SQL and NoSQL databases (e.g., PostgreSQL, MongoDB, Cassandra) to manage structured and unstructured data.
  • Optimize database performance to support machine learning workloads and real-time applications.
  • Implement robust data governance frameworks and ensure data quality assurance practices.
  • Manage and process streaming data to enable real-time decision-making.

    • Leadership & Collaboration :

  • Mentor junior data scientists and assist in technical decision-making to drive innovation.
  • Collaborate with cross-functional teams, including product, engineering, and business stakeholders, to develop solutions that align with organizational goals.
  • Present findings and insights to both technical and non-technical audiences in a clear and actionable manner.
  • Lead proof-of-concept projects and innovation initiatives to push the boundaries of AI / ML applications.

    • Required Qualifications :

    Education & Experience :

  • Masters or PhD in Computer Science, Data Science, Statistics, Mathematics, or a related field.
  • 5+ years of hands-on experience in data science and machine learning, with a focus on real-world applications.
  • 3+ years of experience working with deep learning frameworks and neural networks.
  • 2+ years of experience with cloud platforms and full-stack development.

    • Technical Skills AI / ML :

  • Machine Learning : Proficient in Scikit-learn, XGBoost, LightGBM, and advanced ML algorithms.
  • Deep Learning : Expertise in TensorFlow, PyTorch, Keras, CNNs, RNNs, LSTMs, and Transformers.
  • Large Language Models : Experience with GPT, BERT, T5, fine-tuning, and prompt engineering.
  • Generative AI : Hands-on experience with Stable Diffusion, DALL-E, text-to-image, and text generation

    • models.

  • Agentic AI : Knowledge of multi-agent systems, reinforcement learning, and autonomous agents.

    • Technical Skills Development & Infrastructure :

  • Programming : Expertise in Python, with proficiency in R, Java / Scala, JavaScript / TypeScript.
  • Cloud Platforms : Proficient with AWS (SageMaker, EC2, S3, Lambda), Azure ML, or Google Cloud AI.
  • Databases : Proficiency with SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Cassandra, DynamoDB).
  • Full-Stack Development : Experience with React / Vue.js, Node.js, FastAPI, Flask, Docker, Kubernetes.
  • MLOps : Experience with MLflow, Kubeflow, model versioning, and A / B testing frameworks.
  • Big Data : Expertise in Spark, Hadoop, Kafka, and streaming data processing.

    • Non Negotiables :

  • Cloud Infrastructure ML / AI solutions on AWS, Azure, or GCP.
  • Build and maintain ML pipelines using cloud services (SageMaker, ML Engine, etc.).
  • Implement CI / CD pipelines for ML model deployment and monitoring.
  • Work with both SQL and NoSQL databases (PostgreSQL, MongoDB, Cassandra, etc.).
  • Industry : Must be a BPO or Healthcare Org.

    • (ref : hirist.tech)

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