Data Scientist

Travancore Analytics

0 years

0 Lacs

Kochi, Kerala

Posted:18 hours ago| Platform: SimplyHired logo

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Skills Required

Azure Computer Science Master's degree Databases AWS Bachelor's degree Machine learning AI Communication skills Python

Work Mode

On-site

Job Description

Experience: - Design, develop, and deploy end-to-end machine learning and deep learning models for classification, regression, prediction, and computer vision tasks using TensorFlow, PyTorch, and scikit-learn.
Build and fine-tune transformer-based LLMs (GPT, BERT, LLaMA, etc.) for tasks such as text summarization, chatbots, sentiment analysis, semantic search, and retrieval-augmented generation (RAG) systems.
Apply prompt engineering, chain-of-thought prompting, and synthetic data generation to enhance the performance of generative AI applications.
Collaborate with data engineers to build scalable data pipelines using Spark, Kafka, Hadoop, and Airflow.
Implement model training pipelines and automate hyperparameter tuning, model evaluation, and performance tracking.
Deploy ML models in production environments using AWS, Azure, or GCP, leveraging Docker, Kubernetes, and CI/CD workflows.
Analyze complex datasets, perform statistical analyses, and conduct hypothesis testing, time-series forecasting, and feature engineering.
Visualize and present findings using Tableau, Power BI, or Plotly, creating narratives that influence product and business strategy.
Stay current with trends in LLMs, GenAI, responsible AI, and contribute to thought leadership within and outside the organization.

Skill: - Bachelor's or Master’s degree in Computer Science, Data Science, Statistics, Applied Mathematics, or a related field.
Proficiency in Python, with strong experience in TensorFlow, PyTorch, scikit-learn, and other ML libraries.
Experience with large language models, prompt engineering, Agent development frameworks.
Knowledge of vector databases and semantic search systems.
Familiarity with LLM fine-tuning and parameter-efficient training techniques (e.g., LoRA, PEFT).
Familiarity with big data tools like Spark, Kafka, Hadoop, and workflow orchestration tools like Airflow.
Hands-on experience with cloud platforms (AWS, Azure, or GCP) and deployment tools (Docker, Kubernetes, CI/CD).
Strong foundation in statistics, probability, data modeling, and machine learning theory.
Excellent communication and storytelling skills, with the ability to explain complex concepts to non-technical stakeholders.

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