Daniel Caley Email & Phone Number

San Francisco, Ca, Us

Fairfax, Va, Us

Led the measurement of new feature releases on the site through comprehensive A/B testing, collaborating closely with product managers and mentoring new analysts. My strategic insights were pivotal in driving website growth, both in terms of conversion rates and sales lift. I played a crucial role in the development and refinement of innovative products, such as the 'Group Orders' feature, by continuously releasing and analyzing new enhancements to foster growth in complex and challenging product initiatives.Spearheaded the creation of a Bayesian Shiny dashboard, revolutionizing A/B testing with in-depth feature analysis, enhancing user engagement, improving conversion rates, and streamlining decisions while reducing manual errors.Proved a 25% incrementality in sales team performance through a hypothesis-driven Bayesian A/B testing approach, leveraging inferential statistics, Markov Chain Monte Carlo (MCMC), and R to analyze and transform large datasets.Generate $5 million in additional sales by deploying a supervised machine learning model with Scikit Learn and SQL, successfully identifying and converting potential high-value customers early in the sales process.Achieved a $7 million sales enhancement by architecting and deploying data warehouse tables that connected customer and phone data, with results confirmed by A/B testing methodologies.Increased conversion by 10% by applying Natural Language Processing techniques and Python to wrangle conversation data and apply a semantic sentiment score.

Fairfax, Va, Us

I collaborated with product owners, C-level executives, and VPs to strategize and determine optimal locations for retail store expansion. I developed a predictive model to estimate first-year sales, significantly influencing our store expansion strategy. My expertise in causal inference was key in assessing the performance of new stores, allowing us to optimize investment strategies.Conducted modeling research that leverages Python, SQL, feature engineering, and multilinear regression that helped open 60 retail store locations by predicting first year sales by zip code.Played a pivotal role in proving $40 million in revenue from opening store by designing and implementing a robust causal inference framework, shaping the company’s approach to store expansion.Excelled in a highly collaborative, cross-functional environment, seamlessly bridging engineering and business teams with effective communication of complex data insights, leading to $28 million in incremental sales.Designed a Tableau dashboard that monitors $250 million annually in sales by using descriptive statistics to measure the company’s performance against many KPI’s.

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At this startup, I was charged with creating a diversified investment portfolio, encompassing both traditional assets (stocks, bonds) and non-traditional ones (cryptocurrencies). Leading a team, I established and maintained the portfolio management process, which included tasks such as rebalancing and comprehending various fee structures. My leadership in this innovative financial space was instrumental in navigating the complexities of mixed-asset investment strategies.Led a cross-functional team of researchers and engineers in developing a custom Python portfolio back testing library, integrating financial insights with technical expertise to optimize investment processes.Developed and refined core metrics in a custom analysis dashboard, employing quantile regression models to measure and monitor business performance in investment decisions, providing actionable insights and data-driven recommendations.

Mclean, Va, Us

In the midst of challenging times in the mortgage-backed securities market, I capitalized on the opportunity to redefine the industry leveraging my technical expertise and leadership qualities. My role on the trading floor centered around developing and implementing data-informed strategies for investment and risk management. This approach played a crucial role in stabilizing and advancing the business during a period of economic instability.Utilized advanced SQL and multiple databases to build an Adjustable-Rate Mortgage (ARM) dashboard that tracks individual loan volume, market security volume, and market color to help value and price bonds in an $18 billion market.Leveraged SQL, a thorough understanding of databases, and Python to distribute market prices to a list of mortgage originators saving a trader 30 minutes a day and prevented mistakes caused by user fatigue.Launched the Caley Asset Pooling Engine (CAPE) that helped securitized $320 billion dollars in mortgages and guided complex business decisions by leveraging Visual Basics, SQL, and Python.

Master'S Degree, Data Science

Bachelor Of Science - Bs, Finance