What are the responsibilities and job description for the Data Scientist with QuickSight position at Tricon Solutions?
Data Scientist with QuickSight Knowledge - Twitch Client Office: Santa Clara, California Work Model: Hybrid Type: Contract
Mandatory Skills
Job Description
Roles & Responsibilities
Mandatory Skills
- AWS Bedrock
- Agent Core
- QuickSight
- SQL
- Python
- SQL
- Python
- AWS (QuickSight, S3, Redshift)
- Statistical Analysis
- LangGraph
- 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.
- At least 3 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.