Data Scientist - Python, Tensorflow, SQL, Model Development, ML Lifecycle

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Job Description:

Job Summary:

UPS Enterprise Data Analytics team is looking for a talented and motivated Data Scientist to use statistical modelling, state of the art AI tools and techniques to solve complex and large-scale business problems for UPS operations. This role would also support debugging and enhancing existing AI applications in close collaboration with the Machine Learning Operations team. This position will work with multiple stakeholders across different levels of the organization to understand the business problem, develop and help implement robust and scalable solutions. You will be in a high visibility position with the opportunity to interact with the senior leadership to bring forth innovation within the operational space for UPS. Success in this role requires excellent communication to be able to present your cutting-edge solutions to both technical and business leaderships.

Responsibilities:

• Become a subject matter expert on UPS business processes and data to help define and solve business needs using data, advanced statistical methods and AI
• Be actively involved in understanding and converting business use cases to technical requirements for modelling.
• Query, analyze and extract insights from large-scale structured and unstructured data from different data sources utilizing different platforms, methods and tools like BigQuery, Google Cloud Storage, etc.
• Understand and apply appropriate methods for cleaning and transforming data, engineering relevant features to be used for modelling.
• Actively drive modelling of business problem into ML/AI models, work closely with the stakeholders for model evaluation and acceptance.
• Work closely with the MLOps team to productionize new models, support enhancements and resolving any issues within existing production AI applications.
• Prepare extensive technical documentation, dashboards and presentations for technical and business stakeholders including leadership teams.

Qualifications

• Expertise in Python, SQL. Experienced in using data science-based packages like scikit-learn, numpy, pandas, tensorflow, keras, statsmodels, etc.
• Strong understanding of statistical concepts and methods (like hypothesis testing, descriptive stats, etc.), machine learning techniques for regression, classification, clustering problems, including neural networks and deep learning.
• Proficient in using GCP tools like Vertex AI, BigQuery, GCS, etc. for model development and other activities in the ML lifecycle.
• Strong ownership and collaborative qualities in the relevant domain. Takes initiative to identify and drive opportunities for improvement and process streamline.
• Solid oral and written communication skills, especially around analytical concepts and methods.
• Ability to communicate data through a story framework to convey data-driven results to technical and non-technical audience.
• Master’s Degree in a quantitative field of mathematics, computer science, physics, economics, engineering, statistics (operations research, quantitative social science, etc.), international equivalent, or equivalent job experience.

Bonus Qualifications

• NLP, Gen AI, LLM knowledge/experience
• Knowledge of Operations Research methodologies and experience with packages like CPLEX, PULP, etc.
• Knowledge and experience in MLOps principles and tools in GCP.
• Experience working in an Agile environment, understanding of Lean Agile principles.

Employee Type:
 

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