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Data Scientist/Sr. Data Scientist - AI/ML

2 - 5 years

0 Lacs

Noida Uttar Pradesh India

Posted:4 days ago| Platform: Linkedin logo

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Skills Required

data ai ml drive development cutting healthcare design learning preprocess training testing algorithms model statistics engineering programming clustering autoencoders xgboost preprocessing evaluation score regression pytorch flask api django tensorflow azure aws gcp lstm

Work Mode

On-site

Job Type

Full Time

Job Description

We're seeking a skilled and motivated ML/AI Engineer to join our team and drive end-to-end AI development for cutting-edge healthcare prediction models. As part of our AI delivery team you will be working on designing, developing, and deploying ML models to solve complex business challenges.

Key Responsibilities:

  • Design, develop, and deploy scalable machine learning models and AI solutions.
  • Collaborate with engineers and product managers to understand business requirements and translate them into technical solutions.
  • Analyse and preprocess large datasets for training and testing ML models.
  • Experiment with different ML algorithms and techniques to improve model performance.

Skills & Qualifications:

  • Experience:
    • B.Tech with 2-5 years of relevant experience in Machine Learning, AI, or Data Science roles.
OR
  • M.Tech, M. Statistics with 2-4 years of relevant experiencein Machine Learning, AI, or Data Science roles.
  • Education: Bachelor's/master's degree in computer science or Statistics or any other relevant engineering / AI course from a Tier 1 or Tier 2 college.

Technical Skills:

  • Proficiency in programming languages such asPython & R
  • Strong knowledge of classicalmachine learning algorithms with hands on experience in the following:
    • Supervised (Classification model, regressions models)
    • Unsupervised, (Clustering Algorithms, Autoencoders)
    • Ensemble Models (Stacking, Bagging, Boosting techniques, Random Forest, XGBoost)
  • Experience in data preprocessing, feature engineering, and handling large-scale datasets.
  • Model evaluation techniques like accuracy, precision, recall, F1 score, AUC-ROC for classification, and MAE, MSE, RMSE, R-squared for regression.
  • Explainable AI (XAI) techniques include methods like SHAP values, LIME, feature importance from decision trees, and partial dependence plots.
  • Experience withML frameworkslikeTensorFlow, PyTorch, Scikit-learn,orKeras.
  • Building & deploying Model APIs using framework like Flask, Fast API, Django, TensorFlow Serving etc.
  • Knowledge ofcloud platformslike Azure (preferred), AWS, GCP and experience deploying models in such environments -> changed the wording, added points.

Nice to Have:

  • Object Oriented Programming.
  • Familiarity withNLP, ortime seriesanalysis. -> Moving this into Nice to have, not bare min
  • Exposure todeep learningmodels (RNN, LSTM) and working with GPUs.

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