Title: Senior Data Scientist

Location: Remote

Exp: 6–8 Years

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Key Responsibilities

Machine Learning & Advanced Analytics

Design, develop, validate, and deploy machine learning and statistical models for business-critical applications.

Build supervised and unsupervised learning models including:

Regression models

Classification models

Clustering algorithms

Neural network/deep learning models

Develop predictive modeling solutions for customer behavior, risk scoring, demand forecasting, fraud detection, recommendation systems, and operational optimization.

Build anomaly detection frameworks for identifying unusual patterns, fraud, operational deviations, or system failures.

Design and implement forecasting models using time-series techniques for sales, inventory, demand, and operational planning.

Work on AI/GenAI-driven use cases leveraging Large Language Models (LLMs), prompt engineering, and intelligent automation solutions.

Data Processing & Feature Engineering

Work with large-scale structured and unstructured datasets.

Perform exploratory data analysis (EDA), data cleaning, transformation, and feature engineering.

Build scalable data pipelines and reusable ML workflows.

Optimize model performance using hyperparameter tuning and model evaluation techniques.

Model Deployment & MLOps

Collaborate with engineering teams to deploy ML models into production environments.

Monitor model performance, drift, and retraining strategies.

Implement model versioning, experimentation tracking, and automation workflows.

Collaboration & Stakeholder Management





Partner with business stakeholders to understand business problems and convert them into analytical solutions.

Present insights, findings, and recommendations to technical and non-technical audiences.

Work cross-functionally with data engineers, product managers, business analysts, and software developers.

Required Qualifications

Bachelor's or Master's degree in:

Computer Science

Data Science

Statistics

Mathematics

Engineering

Or related quantitative field

6–8 years of hands-on experience in Data Science, Machine Learning, or Advanced Analytics roles.

Strong understanding of statistical analysis, machine learning algorithms, deep learning concepts, and exposure to GenAI/LLM-based solutions.

Required Technical Skills

Machine Learning & Modeling

Strong experience in

Regression techniques

Linear Regression

Logistic Regression

Regularization methods

Classification algorithms

Decision Trees

Random Forest

XGBoost

SVM

Neural Networks / Deep Learning

ANN

CNN

RNN/LSTM (preferred)

Forecasting and Time Series Modeling

ARIMA/SARIMA

Prophet

LSTM forecasting models

Predictive Modeling

Anomaly Detection techniques

Programming & Tools

Proficiency in Python and/or R

Strong experience with

Pandas

NumPy

Scikit-learn

TensorFlow / PyTorch / Keras

Experience or exposure to GenAI/LLM frameworks and tools such as LangChain, Hugging Face, vector databases, or prompt engineering techniques

Soft Skills

Strong analytical and problem-solving mindset

Excellent communication and stakeholder management skills

Ability to work independently and collaboratively

Robust attention to detail

Ability to manage multiple priorities in a fast-paced environment

📌 Senior Data Scientist (Bengaluru)
🏢 NR Consulting
📍 Bengaluru