Data Scientist

Job Description

Job Details:

We are seeking a highly motivated and enthusiastic Junior Data Scientist with 2-3 years of experience to join our data science team. This role offers an exciting opportunity to contribute to both traditional Machine Learning projects for our commercial IoT platform (EDGE Live) and cutting-edge Generative AI initiatives.

Position: Data Scientist

Division & Department: Enabling Functions_Business Technology Group (BTG)

Reporting To: Customer & Commercial Experience Products Leader

Educational Qualifications

Bachelor's degree in Mechanical, Computer Science, Data Science, Mathematics, or a related field.

Experience

• 2-3 years of hands-on experience with machine learning
• Exposure to Generative AI concepts and techniques, such as Large Language Models (LLMs), RAG Architecture
• Experience in manufacturing and with an IoT platform is preferable
  
  

Role And Responsibilities

• Key Objectives
  
  

Machine Learning (ML)

• Assist in the development and implementation of machine learning models using frameworks such as TensorFlow, PyTorch, or scikit-learn.
• Help with Python development to integrate models with the overall application
• Monitor and evaluate model performance using appropriate metrics and techniques.
  
  

Generative AI

• Build Gen AI-based tools for various business use cases by fine-tuning and adapting pre-trained generative models
• Support the exploration and experimentation with Generative AI models
  
  

Research & Learning

• Stay up-to-date with the latest advancements and help with POCs
• Proactively research and propose new techniques and tools to improve our data science capabilities.
  
  

Collaboration And Communication

• Work closely with cross-functional teams, including product managers, engineers, and business stakeholders, to understand requirements and deliver impactful solutions.
• Communicate findings, model performance, and technical concepts to both technical and non-technical audiences.
  
  

Technical Competencies

• Programming: Proficiency in Python, with experience in libraries like numpy, pandas, and matplotlib for data manipulation and visualization.
• ML Frameworks: Experience with TensorFlow, PyTorch, or scikit-learn.
• Cloud & Deployment: Basic understanding of cloud platforms such as Databricks, Google Cloud Platform (GCP), or Microsoft Azure for model deployment.
• Data Processing & Evaluation: Knowledge of data preprocessing, feature engineering, and evaluation metrics such as accuracy, F1-score, and RMSE.