Job Description

Joining Gadgeon offers a dynamic and rewarding

career experience that fosters both personal and


professional growth. Our collaborative culture

encourages innovation, empowering team members

to contribute their ideas and expertise to


cutting-edge projects.

Data Scientist



The Senior/Lead Data Scientist will design and deploy large-scale analytics solutions that deliver measurable impact. This role leads data-driven projects from ideation through implementation, provides technical and strategic guidance, and ensures best practices in data science across the business.


Key Responsibilities:



Lead end-to-end advanced analytics and data science projects, delivering actionable insights and predictive models. Manage, mentor, and provide guidance to junior and mid-level data scientists. Collaborate with business stakeholders to translate strategic objectives into data-driven solutions and drive the data strategy. Apply advanced statistical, machine learning, and deep learning techniques for problem solving. Oversee data management, data governance, and pipeline design to ensure high data quality and reliability. Develop, validate, and deploy production-grade models for business problems acrossIoT, product analytics, and AI domains. Hands-on solutioning knowledge of Large Language Models (LLMs), fine-tuning, and RAG (Retrieval Augmented Generation) frameworks for enterprise AI applications. Present findings and recommendations to business teams, including creation of clear visualizations and non-technical reports. Stay abreast of the latest data science, analytics, and AI/ML trends and industry best practices.


Required Skills:



7-10 years of experience in data science, analytics, or ML application roles. Expertise with Python, R, SQL, and advanced machine learning libraries (TensorFlow, PyTorch, Scikit-learn). Strong statistical and mathematical modeling background (regression, classification, clustering, deep learning, time series). Hands-on experience with Big Data technologies (Spark) and data pipeline design. Track record of leading successful analytics projects and collaborating cross- functionally. Excellent communication, visualization, and storytelling skills for technical and non-technical audiences. Proven ability to manage teams, mentor junior talent, and foster a collaborative culture.


Preferred Skills



Experience in IoT, product engineering, or high-tech environments. Familiarity with cloud platforms and scalable model deployment (AWS, Azure, GCP). Knowledge of MLOps, containerization (Docker, Kubernetes), and version control (Git). Professional certifications in data science, ML/AI, or project management.


Experience



* 7-10 Years