Data Scientist

Viraaj HR Solutions Private Limited; Khordha; Hybrid; INR 1,400,000 - 2,400,000; Full time

Benefits offered by this job

Hybrid work

Bonuses

Fast promotion

AI training & certifications

Job summary

Viraaj HR Solutions Private Limited is seeking a talented Data Scientist to design, train, and deploy ML models solving business problems across marketing, risk, and operations. You will work with IT and business teams to translate KPIs into data-driven hypotheses.

You will build features, validate models with A/B testing, and communicate insights via Power BI/Tableau, while staying current with ML trends and leveraging cloud platforms (AWS/GCP/Azure).

Qualifications

• Strong Python skills with ML libraries (scikit-learn, pandas, numpy).
• Hands-on experience building ML models and evaluating them.
• Experience connecting data workflows to visualization tools (Power BI/Tableau).

Responsibilities

• Design, train, and deploy ML models to solve business problems.
• Translate KPIs into data-driven hypotheses and validate with statistical methods and A/B tests.
• Collaborate with engineering to productionize models on cloud platforms (AWS/GCP/Azure).
• Develop dashboards to communicate insights to non-technical stakeholders.
• Perform EDA, clean data, and build scalable data pipelines (SQL, Python, PySpark).
• Stay updated with ML advances and propose pilots aligned with business goals.

Skills

Python

Scikit-learn

Pandas

NumPy

SQL

Machine Learning

Statistical Modeling

Power BI

Tools

PySpark

TensorFlow / PyTorch

LLM fine-tuning

Job description

About The Opportunity

A fast-scaling AI & Analytics firm operating at the intersection of enterprise data science and business intelligence, we empower Fortune 500 and mid-market clients across BFSI, Retail, and Healthcare to drive data-led transformation. Our data scientists architect predictive models, automate decision‑making frameworks, and extract actionable insights from petabyte-scale structured and unstructured datasets—deploying solutions that directly impact revenue, cost, and customer experience.

About The Opportunity

A fast-scaling AI & Analytics firm operating at the intersection of enterprise data science and business intelligence, we empower Fortune 500 and mid-market clients across BFSI, Retail, and Healthcare to drive data‑led transformation. Our data scientists architect predictive models, automate decision‑making frameworks, and extract actionable insights from petabyte‑scale structured and unstructured datasets—deploying solutions that directly impact revenue, cost, and customer experience.

Role & Responsibilities

• Design, train, and deploy machine learning models (classification, regression, clustering) to solve core business problems across marketing, risk, and operations.
• Translate business KPIs into data‑driven hypotheses, build feature sets, and validate model performance using statistical rigor and A/B testing.
• Collaborate with engineering teams to productionize models using MLOps pipelines on cloud platforms (AWS/GCP/Azure).
• Develop dashboards and visualisations (Power BI/Tableau) to communicate insights to non‑technical stakeholders with narrative‑driven storytelling.
• Perform exploratory data analysis (EDA), clean raw datasets, and engineer scalable data pipelines using SQL, Python, and PySpark.
• Stay current with emerging ML techniques (LLMs, NLP, time‑series forecasting) and propose innovation pilots aligned with business goals.

Skills & Qualifications

• Must‑Have
• Python
• Scikit‑learn
• Pandas
• NumPy
• SQL
• Machine Learning
• Statistical Modeling
• Power BI
• Preferred
• PySpark
• TensorFlow / PyTorch
• LLM fine‑tuning (HuggingFace, LangChain)

Benefits & Culture Highlights

• Work directly with global clients on high‑impact projects—your models shape real business outcomes.
• Access to continuous upskilling via internal AI labs, Kaggle sponsorships, and certification reimbursements.
• Hybrid work flexibility, performance‑linked bonuses, and rapid promotion paths for top performers.

Skills: python,models,machine learning,data