DATA SCIENTIST I
TE Connectivity
Key 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.
Requirements & Tech Stack
- 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).
Qualifications
- Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, Engineering, Artificial Intelligence, or a related field.
- Internship, academic, or industry experience in ML/AI projects is preferred.
Key Qualities
- Strong 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.




