Data Science and Machine Learning Associate

We are looking for a Data Science & Machine Learning Senior Associate with 3–5 years of relevant experience in data science, machine learning, and analytics. The candidate will be responsible for developing predictive models, analyzing complex datasets, building scalable ML solutions, and supporting production-grade data science applications on cloud platforms.

Key Responsibilities

Develop and implement machine learning and predictive analytics models.

Perform data analysis, statistical modeling, and optimization to solve business problems.

Build demand forecasting and predictive models using time-series and other advanced techniques.

Work with large datasets using Python, SQL, PySpark, and cloud-based data platforms.

Develop and maintain scalable data pipelines for ML model development and deployment.

Implement MLOps practices including model deployment, monitoring, retraining, and data-drift detection.

Collaborate with software engineers, product teams, and business stakeholders to convert business requirements into analytical solutions.

Validate models for accuracy, robustness, bias, and production readiness.

Create meaningful visualizations and communicate analytical insights to technical and non-technical stakeholders.

Required Skills

Python

SQL

Data Science & Machine Learning

Predictive Modeling

Statistical Analysis

Machine Learning Algorithms

Optimization Techniques

Google Cloud Platform (GCP)

BigQuery

Dataflow

Dataproc

Data Fusion

Cloud SQL

Airflow

PySpark

PostgreSQL

Terraform

Tekton

APIs

MLOps

Preferred Skill

Java

Good to Have

Demand Forecasting

Time-Series Analysis

Neural Networks

Ensemble Methods

Support Vector Machines (SVM)

Regression and Cluster Analysis

ML Model Testing

Bias Detection and Data Drift Monitoring

Production ML Deployment

QlikSense

Automotive or Supply Chain Analytics

Education

Bachelor's degree in Computer Science, Data Science, Engineering, Statistics, Mathematics, or a related technical field.Master's degree in a relevant quantitative or technical field is preferred.