Data Scientist

Eucloid Data Solutions; Chennai District; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Eucloid Data Solutions in Chennai is seeking a data scientist to analyze structured and unstructured data, build ML models, and deliver actionable insights for business challenges. You will collaborate with data engineers to deploy and monitor models in production, and communicate results to stakeholders.

A strong background in statistics, Python/R, SQL, and visualization tools is required. This role emphasizes reproducibility, governance, and working in agile teams within a fast-paced

Qualifications

• 3–5 years hands-on experience in data science, ML, or analytics.
• Strong Python or R for analysis and modeling.
• Strong SQL for data extraction and manipulation.
• Experience deploying production ML solutions and ML frameworks.
• Experience with data visualization tools and cloud platforms incl. Databricks.

Responsibilities

• Analyze structured and unstructured datasets to identify actionable insights and trends.
• Develop and deploy machine learning models and statistical solutions for business challenges.
• Apply statistical techniques including hypothesis testing and model evaluation metrics (ROC-AUC, Precision/Recall, RMSE).
• Collaborate with data engineers to design scalable data pipelines and architectures.
• Translate complex data findings into clear, actionable recommendations for stakeholders.
• Contribute to building data-driven tools and dashboards for clients.
• Support deployment, monitoring, and performance tracking of models in production environments.
• Maintain documentation of methodologies, experiments, and results, ensuring reproducibility and governance.
• Work with version control systems and ML lifecycle tools to manage model development and deployment workflows.
• Stay updated on emerging trends in AI/ML and apply learnings to projects.

Skills

Analytical thinking

Communication

Team collaboration

Agile

Problem solving

Education

Bachelor’s or Master’s in Data Science / CS / Statistics

Tools

Python

R

SQL

Tableau

Power BI

Looker

TensorFlow

Scikit-learn

Databricks

Job description

• Analyze structured and unstructured datasets to identify actionable insights and trends.
• Develop and deploy machine learning models and statistical solutions for business challenges.
• Apply statistical techniques including hypothesis testing, probability modeling, and model evaluation metrics (ROC-AUC, Precision/Recall, RMSE, etc.) to ensure robust solutions.
• Collaborate with data engineers to design scalable data pipelines and architectures.
• Translate complex data findings into clear, actionable recommendations for stakeholders.
• Contribute to building data-driven tools and dashboards for clients.
• Support deployment, monitoring, and performance tracking of models in production environments.
• Maintain documentation of methodologies, experiments, and results, ensuring reproducibility and governance.
• Work with version control systems (e.g., Git) and ML lifecycle tools to manage model development and deployment workflows.
• Stay updated on emerging trends in AI/ML and apply learnings to projects.

Qualifications

Academic Background

• Bachelor’s or master’s degree in data science, Computer Science, Statistics or a related field.

Technical Expertise

• 3–5 years of hands‑on experience in data science, machine learning, or analytics.
• Proficiency in Python (e.g., Pandas, NumPy, Scikit-learn) or R for data analysis and modeling.
• Strong SQL skills for data extraction and manipulation.
• Solid understanding of statistics, probability, and model evaluation techniques.
• Experience with machine learning algorithms including regression, classification, clustering, and tree‑based models
• Experience in deploying Production level ML solutions
• Familiarity with ML frameworks (e.g., Scikit-learn, TensorFlow)
• Familiarity with MLOps would be preferred
• Experience with data visualization tools (Tableau, Power BI, Looker).
• Experience with cloud platforms like Databricks preferred.
• Basic understanding of deploying models and working with large‑scale data platforms.

Skills

• Strong problem‑solving mindset and ability to thrive in agile environments.
• Excellent communication skills to convey technical concepts to non‑technical audiences.
• Collaborative spirit, with experience working in cross‑functional teams.
• Ability to translate business requirements into analytical solutions and actionable insights.
• Experience working in production environments with exposure to monitoring and maintaining deployed models.