Senior Data Scientist - Machine Learning

Empaxis Data Management India Private Limited
Multiple Locations
5 - 8 Years

Posted on: 03/06/2025

Job Description

Key Responsibilities :

- Machine Learning Model Lifecycle: Design, develop, deploy, and optimize various machine learning models (supervised, unsupervised, and reinforcement learning) to address complex business challenges.

- Data Analysis & Insight Generation: Conduct in-depth analysis of complex datasets, identifying patterns, trends, and actionable insights that drive data-driven strategies and decision-making.

- Cross-functional Collaboration: Collaborate effectively with cross-functional teams, including engineers, product managers, and business stakeholders, to define problem statements, translate requirements, and integrate data science solutions into production systems.

- Research & Innovation: Stay current with the latest advancements, trends, and research in machine learning, artificial intelligence, and data science. Experiment with new technologies and methodologies to continuously enhance our capabilities.

- Communication & Presentation: Clearly present complex analytical findings, model performance, and strategic recommendations to technical and non-technical audiences.

- Code Quality & Best Practices: Write clean, efficient, and well-documented code, adhering to best practices in data science and software development.


Required Skills & Qualifications :


- 5-8 years of professional experience in data science, machine learning engineering, or a closely related analytical role.

- Proficiency in Python (preferred) or R programming languages, with extensive experience utilizing

relevant data science and machine learning libraries such as:

- scikit-learn

- XGBoost

- TensorFlow

- PyTorch

- Strong theoretical and practical understanding of various machine learning paradigms, including supervised learning, unsupervised learning, and reinforcement learning.

- Solid experience with data manipulation, cleaning, and feature engineering.

- Ability to analyze complex datasets and extract meaningful insights.


- Excellent problem-solving, analytical, and critical thinking skills.

- Strong communication and interpersonal abilities, capable of collaborating effectively within diverse teams.

- Willingness and ability to work in rotational shifts.


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