What are the responsibilities and job description for the Data Analyst Product Analytics & AI Initiatives (SQL, Experimentation, Data Modeling, Airflow - 100/hr W2 position at Projas Technologies, LLC?
We are seeking a Business Data Analyst to support product, customer experience, and AI-driven initiatives. This role will partner closely with business stakeholders to define key performance metrics, develop reporting and dashboards, conduct deep-dive analyses, and design experiments that drive data-informed decision making.
The ideal candidate combines strong analytical skills with business acumen and can effectively translate complex data insights into actionable recommendations for stakeholders.
Key Responsibilities
- Define, refine, document, and maintain business metrics and reporting methodologies.
- Design and execute experiments and A/B tests, including hypothesis creation, success metric definition, test setup, and results analysis.
- Build, maintain, and optimize dashboards and KPI reporting solutions.
- Perform ad hoc analyses and deep-dive investigations to answer business questions and identify opportunities.
- Partner with stakeholders to gather requirements, prioritize requests, and scope analytical projects.
- Investigate and resolve data discrepancies impacting reporting accuracy.
- Communicate findings and recommendations through clear presentations and data storytelling.
- Create and maintain documentation for metrics, reporting logic, and experimentation methodologies.
- Build Foundational Data Structures: Partner directly with senior data science team members to design and build foundational data structures, tracking models, and reporting pipelines for emerging AI-driven product features (including LLM chat interfaces and conversational tools).
- Support Core & Emerging Products: Provide flexible analytical support across high-priority surfaces, balancing focus between new AI initiatives and core application user flows (including primary home screen surfaces and key engagement drivers).
- Adaptable Product Analytics: Serve as a versatile analytical partner across multiple product surfaces to free up capacity for senior data science initiatives, support end-to-end experiment execution, and maintain business-critical KPI reporting.
- Build foundational dataset tables and data models from scratch for newly launched products and services.
- Automate data pipelines using workflow orchestration tools (e.g., Airflow / Composer) to streamline reporting and analytics workflows.
- Conduct midpoint reads and performance tracking on active A/B experiments across AI initiatives and main application screens.
- Serve as analyst across AI products and core app services.
Required Skills
- Advanced SQL querying and data analysis.
- Experience with business intelligence (BI) tools and dashboard development.
- Knowledge of experimentation frameworks, A/B testing, and statistical analysis.
- Requirements gathering and stakeholder management experience.
- Strong analytical thinking and problem-solving skills.
- Excellent communication, presentation, and data storytelling abilities.
- Experience building foundational data structures and dataset models from scratch.
- Hands-on experience or familiarity with data pipeline automation tools (e.g., Airflow, Composer, or similar).
- Strong adaptability and proven track record of rapidly learning and transitioning between new tools and domain areas.
Preferred Qualifications
- Experience supporting product analytics, customer experience, digital platforms, or AI-related initiatives.
- Ability to translate business objectives into measurable metrics and analytical frameworks.
- Experience delivering insights to both technical and non-technical audiences.
- Experience or interest in leveraging generative AI tools (e.g., Claude, ChatGPT, Cursor) or AI agents for query development, scripting, and dashboard automation.
- Background in product analytics within digital platforms, e-commerce, or personal finance domains.
Education
Bachelor's or Master's degree in a quantitative field such as:
- Computer Science
- Statistics
- Applied Mathematics
- Econometrics
- Operations Research
- Data Science or related discipline
SQL, Advanced SQL, Data Analysis, Business Intelligence, BI Tools, Dashboard Development, Dashboard Maintenance, KPI Reporting, Reporting Analytics, Data Visualization, A/B Testing, Experimentation, Hypothesis Testing, Statistical Analysis, Test Design, Success Metrics, Product Analytics, Business Analytics, Data Storytelling, Stakeholder Management, Requirements Gathering, Data Reporting, Metrics Definition, Data Insights, Ad Hoc Analysis, Root Cause Analysis, Data-Driven Decision Making, Analytical Modeling, Quantitative Analysis
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