4Bell Technology

Job Description

We are seeking a highly skilled and experienced Senior Data Scientist to join our advanced analytics and AI team. The ideal candidate will have strong expertise in developing and deploying machine learning and statistical models, with hands-on experience in regression, classification, neural networks, forecasting, predictive analytics, anomaly detection, and emerging AI technologies including Generative AI and Large Language Models (LLMs).

The candidate should possess strong problem-solving abilities, business acumen, and the capability to translate complex data into actionable insights. Experience working on cloud platforms, particularly Google Cloud Platform (GCP), will be an added advantage.

 

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 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