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

• Define and integrate key data sources (internal UPS data and external datasets) to deliver predictive and generative AI models.

• Develop and implement robust data pipelines for cleansing, transformation, and enrichment of large, multi-source datasets.

• Collaborate with data engineering teams to validate and test data pipelines and models during proof-of-concept and production phases.

• Perform exploratory data analysis (EDA) to identify trends, correlations, and actionable patterns that meet business needs.

• Design and deploy generative AI solutions, integrating them into analytics and product development workflows.

• Define and track model KPIs, ensuring ongoing validation, testing, and retraining of models to align with business objectives.

• Create reusable and scalable solutions through clear documentation, process flows, logs, and clean, well-commented code.

• Communicate findings through concise reports, data visualizations, and storytelling to both technical and non-technical stakeholders.

• Present operationalized insights and provide strategic recommendations to business and executive-level stakeholders.

• Apply best practices in statistical modeling, machine learning, generative AI, distributed computing, cloud-based AI, and performance optimization for production deployment.

• Leverage emerging tools, open-source frameworks, and cloud technologies (including Vertex AI, Databricks, and IBM WatsonX) to create predictive and prescriptive analytics solutions.

Required Qualifications

Education:

Bachelor’s degree in a quantitative discipline (e.g., Statistics, Mathematics, Computer Science, Engineering, Operations Research, or related field).

Master’s degree preferred.

Experience:

• Minimum 5+ years of experience in applied data science, machine learning, generative AI, or advanced analytics.

• Proven experience in building and launching moderate-to-large-scale analytics and AI projects into production.

Technical Skills:

• Proficiency in Python, R, and SQL for data preparation, querying, and model development.

• Strong knowledge of supervised, unsupervised, and generative AI techniques such as regression, classification, clustering, causal inference, and large language models (LLMs).

• Hands-on experience with GCP Vertex AI, IBM WatsonX, Databricks, or SageMaker, and frameworks like TensorFlow, PyTorch, and Keras.

• Familiarity with data visualization tools (e.g., Tableau, Power BI, Shiny, D3) to communicate insights effectively.

• Experience working with Linux/Unix and Windows environments.

• Familiarity with Java or C++ is a plus.

Professional Skills:

• Strong analytical skills with attention to detail and a rigorous problem-solving approach.

• Ability to translate complex business problems into high-level AI and analytics solutions.

• Excellent oral and written communication skills, with the ability to explain analytical and generative AI concepts to both technical and non-technical stakeholders.

• Strong storytelling skills to communicate data-driven insights in a clear, impactful way.

Preferred Experience

• Expertise in cloud AI technologies (GCP, IBM WatsonX, AWS, Azure) and modern data pipelines.

• Demonstrated success in implementing generative AI (LLMs, text-to-image, summarization, conversational AI) for business use cases.

• Track record of curiosity and innovation, with the ability to explore complex datasets and generate actionable insights.

  • Background in operations research or quantitative social science is a strong plus.