Senior Data Scientist – Python, R, SQL, GCP, Vertex AI, IBM Watsonx

About the role

The Data Scientist designs, develops and implements advanced analytics and generative AI models to turn large-scale structured and unstructured data into predictive and prescriptive insights. The role works with cross-functional teams to turn business challenges into data-driven solutions, using machine learning, generative AI and data visualization tools, and applies these tools on-premises and in the cloud (including GCP Vertex AI and IBM Watsonx) while promoting data literacy and AI/ML adoption.

Key responsibilities

• Integrate internal UPS data and external datasets to build predictive and generative AI models.
• Build data pipelines for cleansing, transformation and enrichment of large, multi-source datasets.
• Work with data engineering teams to validate and test pipelines and models during proof-of-concept and production.
• Perform exploratory data analysis to find trends, correlations and actionable patterns.
• Design and deploy generative AI solutions within analytics and product workflows.
• Define and track model KPIs, validating, testing and retraining models.
• Document processes, logs and code clearly, and share findings through reports, visualizations and storytelling.
• Present operationalized insights and strategic recommendations to business and executive stakeholders.
• Apply best practices in statistical modeling, machine learning, generative AI, distributed computing and cloud AI, and use tools such as Vertex AI, Databricks and IBM WatsonX.

Required profile

• Bachelor's degree in a quantitative discipline (Statistics, Mathematics, Computer Science, Engineering, Operations Research or related); Master's preferred.
• At least 5 years of experience in applied data science, machine learning, generative AI or advanced analytics.
• Proven experience delivering moderate-to-large-scale analytics and AI projects into production.
• Preferred: expertise in cloud AI (GCP, IBM WatsonX, AWS, Azure), implementation of generative AI (LLMs, text-to-image, summarization, conversational AI), and a background in operations research or quantitative social science.

Required skills

• Python, R and SQL for data preparation, querying and model development.
• Supervised, unsupervised and generative AI techniques, including LLMs.
• Hands-on experience with GCP Vertex AI, IBM WatsonX, Databricks or SageMaker, and TensorFlow, PyTorch and Keras.
• Data visualization tools such as Tableau, Power BI, Shiny or D3.
• Linux/Unix and Windows environments; Java or C++ is a plus.