Overview

Job Title: Data Science and Machine Learning Senior Associate

Responsibilities

• Understand business requirements and analyze datasets to determine suitable approaches to meet analytic business needs and support data-driven decision-making
• Design and implement data analysis and ML models, hypotheses, algorithms and experiments to support data driven decision-making
• Apply various analytics techniques like data mining, predictive modeling, prescriptive modeling, math, statistics, advanced analytics, machine learning models and algorithms, etc.; to analyze data and uncover meaningful patterns, relationships, and trends
• Design efficient data loading, data augmentation and data analysis techniques to enhance the accuracy and robustness of data science and machine learning models, including scalable models suitable for automation
• Research, study and stay updated in the domain of data science, machine learning, analytics tools and techniques etc.; and continuously identify avenues for enhancing analysis efficiency, accuracy and robustness

Qualifications

• Data Science, Big Query,, Data/Analytics, Google Cloud Platform - Biq Query, Data Flow, Dataproc, Data Fusion, TERRAFORM, Tekton,Cloud SQL, AIRFLOW, POSTGRES, Airflow PySpark, Python, API, Machine Learning
• Java
• Senior Associate Exp: 3 to 5 years experience in relevant field
• 3+ years of hands-on experience with Python, SQL, and Machine Learning/Optimization techniques.
• Technical Domain Expertise: Expertise in Predictive Analytical Methods (e.g., Neural Networks, Ensemble Methods, Support Vector Machines) with experience in demand forecasting or market trend analysis.
• Production Experience: 2+ years of experience applying advanced statistical methods (e.g., Multivariate Analysis, Regressions, Cluster Analysis) within production-grade software environments.
• Quality Focus: Experience with testing strategies for ML, including bias detection and robustness checks.
• Software Engineering: Experience deploying and maintaining production software.

Education

• Bachelor's Degree
• Master's Degree
• Education: Bachelor's degree in Computer Science, Computer Engineering, Data Science, or a related technical field.Master’s degree in a quantitative field (e.g., Data Science, Statistics, Operations Research, Engineering, Computer Science) or equivalent professional experience.
• Technical Experience: 3+ years of hands-on experience with Python, SQL, and Machine Learning/Optimization techniques.
• Collaborative Delivery: Experience working within an Agile framework and a proven Proven ability to collaborate with software engineering teams to move models into production.
• Communication: Proven ability to translate real-world business problems into analytical formulations and interpret results for non-analytics partners.
• Advanced Degree: Master’s degree in a quantitative or technical field.
• Technical Domain Expertise: Expertise in Predictive Analytical Methods (e.g., Neural Networks, Ensemble Methods, Support Vector Machines) with experience in demand forecasting or market trend analysis.
• Production Experience: 2+ years of experience applying advanced statistical methods (e.g., Multivariate Analysis, Regressions, Cluster Analysis) within production-grade software environments.
• Quality Focus: Experience with testing strategies for ML, including bias detection and robustness checks.
• Software Engineering: Experience deploying and maintaining production software.
• Cloud Deployment: Experience deploying solutions in a cloud environment (GCP preferred).
• Industry Context: Familiarity with Automotive OEM data, dealer relationships, order fulfillment, or large-scale supply chain logistics.