Senior Advisory Data Engineer

Key Skills

Aartificial intelligence, Amazon Simple Storage Service (S3), API, AWS, AWS Sagemaker, Data Engineering, Data science techniques, Data security, Docker, ETL frameworks, Generative AI, Kubernetes-K8s, Lambda, Machine learning techniques, MLflow, MLOps tools, Natural Language Processing (NLP), Python Programming, PyTorch, R Programming, Scikit-learn, TensorFlow

Job Description

We are looking for a highly skilled and motivated Data Science Platform Developer who will be responsible for creating and maintaining a robust platform for data science development and deployment. The ideal candidate should have a deep understanding of industry trends in data science and AI, possess strong software development skills, and be able to design and implement innovative features in our machine learning platform.

The Job

• Platform Development: Develop, enhance, and maintain a state-of-the-art data science platform that supports the end-to-end data science lifecycle, from data ingestion and preprocessing to model training and deployment.
• Innovative Features: Stay updated with the latest trends and advancements in data science and AI and implement cutting-edge features and tools in the platform to facilitate advanced analytics and machine learning.
• Production-Grade Solutions: Build and optimize solutions that are production-ready, scalable, and reliable, ensuring seamless deployment of data science models into real-world applications.
• Collaboration: Collaborate with cross-functional teams, including data scientists, engineers, and product managers, to understand their needs and translate them into platform features and capabilities.
• Security and Compliance: Ensure data security and compliance with relevant industry standards and regulations, implementing security measures to protect sensitive data.
• Performance Optimization: Continuously monitor and improve the platform's performance, scalability, and efficiency to meet the growing demands of data science projects.
• Documentation: Create clear and comprehensive documentation for platform features, APIs, and best practices to facilitate ease of use for internal and external users.
• Technical Support: Provide technical support to data science teams and end-users, troubleshoot issues, and offer guidance on platform usage

Required Qualifications & Skills

• UG - B.Tech/B.E. OR PG – M.S. / M.Tech in Computer Science, Engineering or related discipline
• 10 - 12 years’ experience in software development, with a focus on data science platforms, machine learning, and AI.

Must have:

• Expertise in AWS, specifically API Gateway, Lambda, Sagemaker, S3, AI services.
• Experience in MLOps, should have experience in training, inferencing of data science models
• Should have experience in Machine learning pipelines (MLFlow, TensorFlow, Sagemaker)
• Experience in Data Science/ Artificial Intelligence projects involving Generative AI, NLP, TensorFlow, PyTorch, scikit-learn
• Strong programming skills in languages such as Python, R
• Experience with containerization technologies (e.g., Docker, Kubernetes)
• Familiarity with data engineering concepts, including data pipelines and ETL processes
• Should have experience in designing highly scalable, highly available, cost optimized production systems
• Self-Driven, should have highly analytical, critical thinking ability & problem-solving skills

www.pitneybowes.com

Good to have:

• Experience working on Data Apps – Streamlit, Dash App
• Experience in simulation
• Experience deploying models on edge

We will:

• Provide the will: opportunity to grow and develop your career

• Offer an inclusive environment that encourages diverse perspectives and ideas
• Deliver challenging and unique opportunities to contribute to the success of a transforming organization
• Offer comprehensive benefits globally (PB Live Well)

Pitney Bowes is an equal opportunity employer that values diversity and inclusiveness in the workplace.