Job Overview

- Strong proficiency in Python for data analysis and machine learning.
- Good knowledge of SQL and relational databases.
- Understanding of Machine Learning algorithms, including: Regression, Classification, Clustering.
- Recommendation Systems: Time Series Forecasting
- Experience with AI/ML libraries such as: Scikit-learn, Pandas, NumPy, TensorFlow or PyTorch (basic knowledge)
- Understanding of statistics, probability, hypothesis testing, and feature engineering.
- Data visualization skills using Power BI, Tableau, Matplotlib, or Seaborn.
- Basic knowledge of Generative AI and Large Language Models (LLMs).
- Familiarity with cloud platforms such as AWS, Azure, or Databricks is an advantage.

Responsibilities

- Develop and validate machine learning models to address business challenges.
- Perform data exploration, cleansing, feature engineering, and model evaluation.
- Analyze large datasets to identify trends, patterns, and business opportunities.
- Support deployment and monitoring of ML models in production environments.
- Build dashboards, reports, and visualizations to communicate insights.




- Collaborate with business stakeholders to understand requirements and translate them into analytical solutions.
- Conduct experiments and evaluate model performance using appropriate metrics.
- Document methodologies, assumptions, and results for knowledge sharing.
- Stay updated with new developments in AI, ML, and data science technologies.

Education Experience

- Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Artificial Intelligence, or a related field.
- 0-3 years of experience in Data Science, Analytics, Machine Learning, or AI-related projects.
- Internship, academic, or industry experience in ML/AI projects is preferred.

Key Qualities

- Solid analytical and problem-solving skills.
- Curiosity and willingness to learn new technologies.
- Good communication and presentation skills.
- Ability to work collaboratively in cross-functional teams.
- Attention to detail and quality.
- Self-motivated with a continuous improvement mindset.
- Results-oriented and customer-focused.

Competencies

- Values: Integrity, Accountability, Inclusion, Innovation, Teamwork

📌 DATA SCIENTIST I (Bengaluru)
🏢 TE Connectivity
📍 Bengaluru