Data Scientist

Quantzig; Thousand Oaks (CA); On-site; USD 110,000 - 170,000; Full time

Job summary

Quantzig is seeking a Senior Data Science Analyst to oversee data pipelines and turn complex data into trusted business insights. You will help build and scale the Neural Nexus Platform, turning information into actionable intelligence for executives.

You will prototype and productionize AI agents that synthesize data, identify trends, answer business questions, and support decision-making, while enforcing data quality, governance, and responsible-AI guardrails.

Qualifications

• Doctorate or Master's or Bachelor's with relevant experience in data science, analytics, or a related field.
• Proven ability to design scalable data pipelines and translate business questions into analytics.
• Experience building executive dashboards and AI-enabled products.

Responsibilities

• Design and maintain scalable data pipelines, curated datasets, and reporting layers using SQL, Python, Databricks, APIs, and cloud platforms.
• Integrate structured and unstructured data from various sources for dashboards and analytics.
• Create data models supporting executive dashboards and scorecards; deliver business reviews.

Skills

SQL

Python

APIs

Data storytelling

Education

Doctorate degree

Master's degree

Bachelor's degree

Tools

Databricks

Power BI

Tableau

Git

Job description

This is a business-facing data analyst / scientist role focused on overseeing data pipelines and turning complex information into trusted, actionable insight. In this role, you will help build and scale the Neural Nexus Platform — an enterprise data and AI capability that transforms complex information into trusted, actionable business insights.

You will build data pipelines that integrate structured and unstructured data into executive dashboards and analytical products, and you will prototype and productionize AI agents that synthesize information, identify trends, answer business questions, and support executive decision-making.

RESPONSIBILITIES INCLUDE

• Design and maintain scalable data pipelines, curated datasets, and reporting layers using SQL, Python, Databricks, APIs, and cloud-based platforms.


• Integrate and process structured and unstructured data from databases, enterprise systems, documents, presentations, collaboration platforms, and external sources.


• Create trusted data models that support executive dashboards, scorecards, and recurring business reviews.


• Partner with business and technical stakeholders to translate business questions into practical data, analytics, and AI solutions.


• Prototype and deploy AI agents using large language models, retrieval-augmented generation, semantic search, and workflow orchestration.


• Establish data-quality controls, AI evaluation methods, monitoring, access controls, and responsible-AI guardrails.


• Apply software engineering best practices, including automated testing, version control, CI/CD, documentation, and production monitoring.


• Communicate technical recommendations and business insights clearly while providing effective documentation and knowledge transfer.

WHAT WE EXPECT OF YOU

The Senior Data Science Analyst we seek is an independent, collaborative, and delivery-oriented technical leader who thrives in ambiguity and engages confidently with executive audiences.

BASIC QUALIFICATIONS

• Doctorate degree and 2 years of relevant experience; or


• Master's degree and 4 years of relevant experience; or


• Bachelor's degree and 6 years of relevant experience.

PREFERRED QUALIFICATIONS

Experience working within a cross-functional digital product team and collaborating with product managers, designers, engineers, data scientists, and business stakeholders to deliver and continuously improve data and AI products.

• Advanced proficiency in SQL and Python for data engineering, automation, analytics, and AI development.


• Hands-on experience with Databricks or a comparable platform, including ETL/ELT workflows, Delta Lake, Apache Spark or PySpark, and cloud data architecture.


• Analytical data models and executive dashboards built with Power BI, Tableau, or similar tools.


• Unstructured data and AI agents using large language models, retrieval-augmented generation, embeddings, vector search, and tool calling.


• Prototype-to-production delivery moving data and AI solutions from rapid prototype to secure, scalable, and monitored production deployment.


• Cloud and engineering practices familiarity with Azure, AWS, or Google Cloud, as well as Git, automated testing, CI/CD, and data governance practices.


• Communication and data storytelling with the ability to work independently, manage ambiguity, and engage executive audiences.


• Regulated-industry experience in pharmaceutical, biotechnology, healthcare, or another regulated environment is preferred.