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Data Scientist-Artificial Intelligence

Data Scientist-Artificial Intelligence

IBM

3 - 7 years

14 - 18 Lacs

mumbai

Posted:Just now| Platform:

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Skills Required

python ml algorithms tensorflow pytorch statistics algorithms cnn natural language processing vertex scikit-learn aws sagemaker numpy machine learning azure devops data bricks pandas spark gcp computer vision hadoop aws big data data wrangling ml

Work Mode

Work from Office

Job Type

Full Time

Job Description

Role Overview

We are seeking a Machine Learning Data Scientist with hands-on experience in building, training, and deploying ML models that solve real-world business problems. The ideal candidate should be proficient in ML algorithms, feature engineering, model evaluation, and deployment, with strong programming and statistical skills.

Key Responsibilities

Work with stakeholders to understand business problems and translate them into ML solutions.
Perform data exploration, cleaning, and feature engineering for structured and unstructured datasets.
Build and validate models using algorithms for classification, regression, clustering, recommendation, NLP, or CV as applicable.
Use Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch) for ML workflows.
Deploy models into production via ML pipelines (MLflow, SageMaker, Azure ML, or equivalent).
Track and evaluate models using MLOps practices (versioning, reproducibility, monitoring).
Present insights and recommendations to business teams with visualizations and storytelling.

Required education

Bachelor's Degree

Preferred education

Master's Degree

Required technical and professional expertise

Mandatory Skills

Strong proficiency in Python for ML.
Good understanding of statistics, probability, and hypothesis testing.
Experience with ML frameworks (Scikit-learn, TensorFlow, PyTorch).
Hands-on with data wrangling, feature engineering, and preprocessing.
Practical experience with at least one cloud ML platform (Azure ML, AWS SageMaker, or GCP Vertex AI).
Experience with model deployment and lifecycle management (MLflow or similar).

Preferred technical and professional experience

Good to Have

Experience with NLP (transformers, embeddings) or Computer Vision (CNNs).
Exposure to Databricks MLflow & Feature Store.
Familiarity with big data frameworks (Spark, Databricks, Hadoop).
Experience with real-time ML inference pipelines.

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Data Scientist-Artificial Intelligence