Data Scientist

Elabs Infotech; Hyderabad; On-site; INR 1,200,000 - 2,200,000; Full time

Job summary

Elabs Infotech seeks a skilled Data Scientist to develop predictive models, analyze large datasets, and deliver data-driven insights using Python and ML techniques. The role emphasizes model development, data preprocessing, and deploying ML solutions to solve business problems.

The ideal candidate will perform EDA, feature engineering, and collaborate with stakeholders to translate requirements into analytical solutions, while maintaining production ML models and producing dashboards for

Qualifications

• Strong Python programming and data preprocessing skills.
• Experience with ML and DL models.
• Experience with structured and unstructured data.
• Proficient in SQL for data extraction.
• Experience with model deployment via REST APIs or cloud.
• Familiar with EDA and statistics.
• Version control with Git; Linux environment familiarity.
• Familiar with ML tools and frameworks.

Responsibilities

• Analyze datasets to identify trends and insights.
• Design, build, and deploy ML/DL models.
• Develop data pipelines for collection, cleansing, transformation, feature engineering.
• Perform EDA and statistical analysis.
• Build predictive, classification, clustering, and recommendation models.
• Write Python code for data processing and model development.
• Tune hyperparameters and feature selection.
• Collaborate with stakeholders to translate requirements into analytical solutions.
• Deploy models via REST APIs or cloud platforms.
• Monitor and maintain production ML models.
• Prepare dashboards and reports.

Skills

Python

Pandas

NumPy

Scikit-learn

TensorFlow

PyTorch

SQL

Data Visualization

Git

Linux

REST APIs

EDA

Education

Bachelor's or Master's in CS/DS/Statistics

Tools

Git

Linux

Docker

Kubernetes

AWS

Azure

GCP

Power BI

Tableau

MLflow

Job description

Job Summary

We are seeking a skilled Data Scientist with strong expertise in Python and Machine Learning to develop predictive models, analyze large datasets, and deliver data-driven insights. The ideal candidate should have experience in statistical analysis, data preprocessing, model development, and deploying machine learning solutions to solve business problems.

Key Responsibilities

• Analyze structured and unstructured datasets to identify trends and business insights.
• Design, build, and deploy Machine Learning and Deep Learning models.
• Develop data pipelines for data collection, cleansing, transformation, and feature engineering.
• Perform exploratory data analysis (EDA) and statistical analysis.
• Build predictive, classification, clustering, and recommendation models.
• Write efficient Python code for data processing and model development.
• Optimize model performance using hyperparameter tuning and feature selection.
• Collaborate with business stakeholders to understand requirements and translate them into analytical solutions.
• Deploy machine learning models using REST APIs or cloud platforms.
• Monitor, maintain, and improve production ML models.
• Prepare dashboards and reports to communicate insights to stakeholders.
• Follow best practices for model versioning, documentation, and reproducibility.

Required Skills

• Strong programming skills in Python
• Experience with Pandas, NumPy, Scikit-learn
• Knowledge of TensorFlow or PyTorch
• Experience in Machine Learning algorithms:
• Regression
• Classification
• Clustering
• Recommendation Systems
• Time Series Forecasting
• Strong SQL skills for data extraction and analysis
• Experience in Data Visualization using Matplotlib, Seaborn, Plotly, or Power BI/Tableau
• Hands-on experience with feature engineering and model evaluation
• Understanding of statistics, probability, and hypothesis testing
• Experience with Git and version control
• Familiarity with Linux environments

Preferred Skills

• Experience with Generative AI and Large Language Models (LLMs)
• Knowledge of LangChain, Hugging Face, or OpenAI APIs
• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP)
• Knowledge of Docker and Kubernetes
• Experience with Apache Spark or PySpark
• Familiarity with MLOps tools such as MLflow, Kubeflow, or SageMaker

Qualifications

• Bachelor"s or Master"s degree in Computer Science, Data Science, Statistics, Mathematics, Artificial Intelligence, or a related field.
• 37 years of experience in Data Science, Machine Learning, or AI development.