Senior Data Scientist

Title: Senior Data Scientist
Location: Remote
Exp: 6 8 Years

Job Description:
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
Strong attention to detail
Ability to manage multiple priorities in a fast-paced environment