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Diverse Lynx
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AIML Data Scientist

AIML Data Scientist

Diverse Lynx

3 - 5 years

5 - 7 Lacs

chennai

Posted:2 days ago| Platform:

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Skills Required

computer science deep learning data science gcp machine learning programming data mining statistics sql python

Work Mode

Work from Office

Job Type

Full Time

Job Description

Hiring for AIML Data Scientist - Bangalore

Job Summary:

We are looking for a highly skilled and motivated

AI/ML Data Scientist

to join our team. The ideal candidate will be responsible for building, evaluating, and deploying scalable machine learning models and AI-driven solutions to solve complex business problems. You should have a strong background in statistics, machine learning, deep learning, data engineering, and software development.

Key Responsibilities:

Design, develop, and deploy machine learning models for classification, regression, clustering, NLP, and recommendation systems.
Collect, clean, and preprocess large datasets from diverse sources.
Use statistical analysis and data mining techniques to extract insights and identify patterns.
Develop and maintain data pipelines and model training workflows.
Collaborate with cross-functional teams including engineers, product managers, and business stakeholders to define and deliver AI/ML solutions.
Monitor model performance in production and implement improvements as necessary.
Stay up-to-date with the latest trends and technologies in AI/ML research and applications.
Document methodologies, experiments, and results clearly and effectively.

Required Qualifications:

Bachelors or Masters degree in Computer Science, Data Science, Mathematics, Statistics, or a related field.
3-5 years of experience in machine learning, data science, or AI.
Strong programming skills in Python (preferred), R, or Java.
Experience with ML frameworks such as TensorFlow, PyTorch, scikit-learn, XGBoost, etc.
Proficiency in SQL and working with large-scale data (e.g., Hadoop, Spark).
Solid understanding of statistics, probability, and algorithms.
Experience deploying models into production (e.g., using Docker, Flask, FastAPI, MLflow).
Familiarity with cloud platforms (AWS, GCP, or Azure) is a plus.

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