Data Scientist with QuickSight

Job Title: Data Scientist with QuickSight

Location: Santa Clara, California -Hybrid: Yes

Duration: Long Term Contract

Mandatory skills: AWS Bedrock, Agent Core,  QuickSight, SQL, and Python 

Mandatory Skills: SQL, Python, AWS (QuickSight,S3, Redshift), statistical analysis, Lang Graph, Agentic AI, Generative AI

Job Description

• Become a domain expert in the company''s customer support operations and platform data, developing a strong understanding of how the business operates and where value is created.
• Translate ambiguous business questions into clear, actionable analyses and solid deliverables; define metrics that measure customer support effectiveness and operational performance.
• Build and maintain dashboards that surface key insights for stakeholders across support and analytics functions.
• Design and apply statistical methods to evaluate program effectiveness, support operational decisions, and identify trends in customer and user behavior.
• Leverage LLM- and agent-based approaches to automate recurring analyses, accelerate data exploration, and build self-serve tools that let stakeholders query and interpret data without manual intervention.
• Produce ad-hoc analyses and reports that help teams make time-sensitive decisions with confidence.
• Communicate findings clearly to both technical and non-technical partners; distill complex data into concise, actionable insights.

Roles & Responsibilities

• Experience in Analytics, Data Science, Statistics, Mathematics, or equivalent industry experience.
• Atleast 5+ years of experience as a data scientist or data analyst in a data-driven environment.
• Strong SQL skills with the ability to write and optimize complex queries.
• Working proficiency in Python for data analysis and automation.
• Experience building dashboards and data visualizations (AWS QuickSight preferred).
• Background in statistical design and analysis (e.g., experiment design, hypothesis testing, regression).
• Ability to take mid-to-complex tasks from ambiguity through to delivered results with minimal hand-holding.
• Strong communication skills with a track record of creating insights that influence decisions.
• Some experience working within AWS environments (e.g., S3, Redshift).
• Hands-on experience with LLMs and agentic AI concepts — prompt engineering, retrieval-augmented generation (RAG), and building or integrating agent workflows (e.g., tool use / function calling, orchestration frameworks such as LangGraph, or protocols like MCP).
• Familiarity with applying agentic patterns to real analytics use cases (e.g., text-to-SQL, automated report generation, or conversational data assistants) is a strong plus.