Data Scientist(india)

TalentKloud Holding LLC
yesterday

Role details

Contract type
Permanent contract
Employment type
Part-time (≤ 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

Tech stack

Amazon Web Services (AWS)
Data analysis
Artificial Neural Networks
Azure
Big Data
Data Cleansing
Information Engineering
Python
Machine Learning
NumPy
Performance Tuning
TensorFlow
Feature Engineering
Data Ingestion
PyTorch
Large Language Models
Deep Learning
Keras
Pandas
Scikit Learn
Kubernetes
Machine Learning Operations
Recurrent Neural Networks
Docker

Job description

  • Train and optimize Deep Neural Network architectures for Regression and Industrial Control use cases
  • Design and implement end-to-end Machine Learning and Deep Learning pipelines including data ingestion, data cleaning, feature engineering, model training, deployment, and monitoring
  • Work with large and complex datasets for preprocessing, exploratory data analysis (EDA), and feature engineering
  • Apply Regression Models and Predictive Analytics to solve business problems
  • Develop Time Series and Forecasting models for trend prediction and risk estimation
  • Collaborate with cross-functional teams to integrate ML solutions into production environments

Requirements

We are looking for a highly skilled Data Scientist with strong expertise in Machine Learning, Deep Learning, and production-grade ML systems to solve complex real-world business challenges., * Deep Learning (Neural Networks, CNN, RNN, LSTM, Transformers)

  • PyTorch, TensorFlow, Keras
  • Python Programming
  • Scikit-learn
  • Pandas and NumPy
  • Machine Learning (Regression, Classification, Ensemble Models)
  • Time Series Forecasting and Predictive Modeling
  • Model Training, Hyperparameter Tuning, and Cross Validation

Good to Have:

  • Cloud Platforms: AWS, Azure, or GCP
  • MLOps Tools: Docker, Kubernetes, MLflow, Seldon, etc.
  • Exposure to Big Data and Data Engineering
  • Experience with NLP, GenAI, or LLMs

Location : Remote

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