Data and AI thought leadership: You will use data to understand the product and business ecosystem, quantify new opportunities through data and AI techniques, identify upcoming challenges, and shape product development to bring value to users, business divisions, and First Americans. You will help develop data and AI strategy and support leadership in prioritizing what to build and setting goals for execution.
Product Analytics: You will guide product teams using AI, data, and insights. You will focus on developing hypotheses and employ a diverse toolkit of rigorous analytical approaches, different methodologies, frameworks, and technical and/or AI approaches to test them. Additionally, you will work with corporate reporting teams to ensure business division reports are maintained and enhanced as the suite of products is rolled out.
Communication and Influence: You will not simply present data but tell data-driven stories. You will convince and influence leaders using clear insights and recommendations. You will build credibility through structure and clarity and be a trusted strategic partner.
Requirements & Skills:
10+ years of experience working with data, including data mining, statistical analysis, predictive modeling, and experience leading data-driven initiatives and teams
2+ years of experience working with artificial intelligence (AI) techniques such as any of the following: machine learning, deep learning, and natural language processing, applying these techniques to solve complex business problems
Proficiency with data analysis tools (e.g., Python, SQL, Power BI, Snowflake, Looker) and data visualization techniques
Strong analytical, quantitative, and problem-solving skills, with the ability to transform complex data into actionable insights
Experience ensuring data quality, integrity, and adherence to governance and security best practices
Experience with artificial intelligence methodologies such as machine learning, generative AI, and large language models
Effective communication and collaboration skills, with the ability to influence cross-functional teams such as product, Product Marketing, Engineering, and Design
Track record owning and driving data roadmap strategy and execution for a product-led organization
Experience working in a highly regulated industry like Real Estate or Financial Services (if applicable)
Drive analytics projects end-to-end in partnership with Product, Design, Product Marketing, Engineering, and cross-functional business division teams to inform, influence, support, and execute product strategy and investment decisions.
Developand execute data science and AI vision, strategy, roadmap, and solutions to identify opportunities for product improvements, new product features, improve and forecast growth, and improve product use and customer experience.
Design metrics and KPI definitions with goals for different product areas, report and communicate insights around product success to partners and the senior management team.
Oversee the design, development, and implementation of advanced analytics and AI models and algorithms to extract valuable insights from large and complex datasets.Solve a wide array of challenging problems using different analytical and statistical approaches.
Lead data exploration, hypothesis testing, and statistical analysis to identify trends, patterns, and correlations for business optimization.
Find opportunities and launch AI initiatives such as Generative AI, to automate processes and solve unarticulated business problems.
Serve as a thought partner for product managers, engineering managers, and leadership in influencing the product insights roadmap and strategy by identifying opportunities through deep-dive analyses and/or modeling.
Partner closely with internal data engineering teams to improve data assets, quality, metrics and insights and proactively identify opportunity areas for deep dive investigations and future program development. Analyze and validate data to ensure high data quality and reliable insights.
Contribute towards advancing the Data Analytics, Data Science and AI discipline, including but not limited to driving data best practices (e.g. analysis, goaling, experimentation), improving analytical processes, scaling AI knowledge and tools, and mentoring team members.
