SR. DATA SCIENTIST

Overview

Solves complex problems and help stakeholders make data- driven decisions by leveraging quantitative methods, such as machine learning. It often involves synthesizing large volume of information and extracting signals from data in a programmatic way.

Roles & Responsibility

RESPONSIBILITIES :

Technical Strategy & Leadership

• Define and lead the technical roadmap for machine learning, deep learning, LLMs, and AI initiatives.
• Architect end-to-end ML pipelines including data ingestion, feature engineering, model training, evaluation, deployment, and monitoring.
• Mentor junior data scientists and provide technical guidance across modeling, experimentation, and best coding practices.
• Establish standards for model governance, explainability, reproducibility, and documentation.
  
  

Machine Learning & Predictive Modeling

• Oversee the design, development, and deployment of supervised and unsupervised learning models, including classification, regression, forecasting, clustering, and anomaly detection.
• Implement feature engineering, model optimization, hyperparameter tuning, and MLOps practices for scalable production systems.
• Conduct A/B experiments, evaluate model performance, and ensure robustness, fairness, and compliance.
• Lead initiatives involving Large Language Models (LLMs), Generative AI, and Agentic AI to enable content creation, workflow automation, and autonomous decision-making.
• Fine-tune, evaluate, and deploy foundational models and multimodal AI architectures.
• Build conversational agents, recommendation engines, and knowledge reasoning systems leveraging transformer-based models.
• Deep Learning & Computer Vision
• Drive research and application of ANNs, RNNs/LSTMs/Transformers, Computer Vision, and Transfer Learning techniques for sequential, image, and multimodal data.
• Develop and optimize architectures for tasks such as object detection, segmentation, OCR, time-series prediction, and embeddings.
• Deploy deep learning models on cloud environments or edge devices using optimized runtimes (TensorRT, ONNX, etc.).
  
  

Data Engineering & MLOps

• Collaborate with data engineering teams to design scalable data pipelines and cloud architectures (AWS/Azure/GCP).
• Implement CI/CD pipelines for ML, model monitoring systems, and automated retraining workflows.
• Ensure data quality, governance, and compliance with security and privacy standards.
  
  

Desired Candidate Profile:

Master’s in Computer Science, Data Science, Machine Learning, Statistics, or related field.

Qualifications & Experience

• 6+ years of experience in machine learning, deep learning, natural language processing, or applied AI.
• Strong proficiency in Python, ML/DL frameworks (TensorFlow, PyTorch, Scikit-learn), and data pipelines.
• Experience deploying ML models to production environments (Docker, Kubernetes, MLflow, SageMaker, Vertex AI, etc.).
• Strong understanding of statistical modeling, optimization, and experimental design.
• Experience with LLMs, vector databases, RAG pipelines, and model fine-tuning.
• Hands-on experience with Computer Vision, transformers, sequence modeling, and multimodal architectures.
• Familiarity with MLOps, distributed training, and big-data ecosystems (Spark, Databricks, Snowflake).
• Strong communication, leadership, and cross-team collaboration skills.
  
  

• Demonstrate Customer Focus
• Communicate Effectively
  
  

Values: Integrity, Accountability, Inclusion, Innovation, Teamwork

About Te Connectivity

TE Connectivity plc (NYSE: TEL) is a global industrial technology leader creating a safer, sustainable, productive, and connected future. As a trusted innovation partner, our broad range of connectivity and sensor solutions enable the distribution of power, signal and data to advance next-generation transportation, energy networks, automated factories, data centers enabling artificial intelligence, and more.

Our more than 90,000 employees, including 10,000 engineers, work alongside customers in approximately 130 countries. In a world that is racing ahead, TE ensures that EVERY CONNECTION COUNTS. Learn more at www.te.com and on LinkedIn, Facebook, WeChat, Instagram and X (formerly Twitter).

What Te Connectivity Offers

We are pleased to offer you an exciting total package that can also be flexibly adapted to changing life situations - the well-being of our employees is our top priority!

• Competitive Salary Package
• Performance-Based Bonus Plans
• Health and Wellness Incentives
• Employee Stock Purchase Program
• Community Outreach Programs / Charity Events
• Employee Resource Group
  
  

TE Connectivity has become aware of fraudulent recruitment activities being conducted by individuals or organizations falsely claiming to represent TE Connectivity. Please be advised that TE Connectivity never requests payment or fees from job applicants at any stage of the recruitment process. All legitimate job openings are posted exclusively on our official careers website at te.com/careers, and all email communications from our recruitment team will come only from actual email addresses ending in @te.com. If you receive any suspicious communications, we strongly advise you not to engage or provide any personal information, and to report the incident to your local authorities.

Across our global sites and business units, we put together packages of benefits that are either supported by TE itself or provided by external service providers. In principle, the benefits offered can vary from site to site.