Live opening · Posted 9 days ago

AI/ML Data Scientist

HYrEzy Tech Solutions · India (Remote)
Linkedin No
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At a glance

The key details from the original listing.

Posted 9 days ago
CompanyHYrEzy Tech Solutions
LocationIndia (Remote)
Salary2.4M INR/yr - 3.8M INR/yr
Work modeNo
SourceLinkedin
Listed9 days ago

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About the role

Description supplied by the original job listing.

AI/ML Data Scientists
Department: Data Science & Advanced Analytics
Experience Required: 4 to 8 Years
Compensation (Market Standard): INR 2,400,000 to 3,800,000 Per Annum (CTC)
Locations: Bangalore / Pune / Hybrid / Remote-flexible across India
Role Overview & Key Responsibilities
We are looking for a talented AI/ML Data Scientist to build predictive analytical models, time-series forecasting engines, and machine learning solutions that drive enterprise decision-making. In this role, you will analyze complex, large-scale datasets, engineer powerful predictive features, and collaborate with software engineering teams to embed statistical and machine learning models directly into customer-facing software products.
Model Development: Design, train, evaluate, and optimize machine learning and deep learning models for classification, regression, clustering, and predictive forecasting.
Feature Engineering: Extract, clean, transform, and engineer high-value predictive features from massive unstructured and structured datasets.
ML Pipeline Automation: Build robust, end-to-end data ingestion and model training pipelines utilizing MLOps best practices and automated retraining scripts.
Model Validation & Tuning: Conduct rigorous hyperparameter tuning, cross-validation, and bias-variance analysis to ensure production models maintain accuracy and stability.
Business Insights Translation: Translate complex statistical findings and predictive metrics into clear visual dashboards, strategic reports, and actionable business recommendations.
Required Skills & Experience
Educational Background: Master’s or Bachelor’s degree in Statistics, Mathematics, Computer Science, Data Science, or a related quantitative discipline.
Technical Proficiency: Expert-level coding skills in Python, utilizing core data science libraries such as Pandas, NumPy, Scikit-Learn, PyTorch, or TensorFlow.
Statistical Expertise: Strong foundation in probability, statistical testing, hypothesis validation, and time-series modeling methodologies.
Collaboration Tools: Experience working with SQL databases, Git version control, and cloud-hosted data platforms (Snowflake, BigQuery, or AWS Redshift).
Skills: numpy,features,learning,ml,datasets,tensorflow,validation,machine learning,models,pytorch,forecasting,scikit-learn,data science,pandas

Work arrangement
No

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