Data Scientist at YapStone
Walnut Creek, CA, US

Developing innovative technologies to revolutionize the payments industry while helping customers transact in global marketplaces is not for the faint of heart.  We have big goals and are looking for people to join our team who want to leave a legacy. Just as you are committing to do your best work, Tom our CEO, commits to making this the best place you’ve ever worked. It’s a partnership from the very beginning.  If you are looking to step outside your comfort zone, learn new things, apply your skills, collaborate with brilliant people and have fun along the way, then you might be our next Yapster!  We promise to provide you with an amazing journey along your career.  At Yapstone, we don’t just accept difference — we celebrate it, we support it, and we thrive on it for the benefit of our employees. Yapstone is proud to be an equal opportunity workplace.

We are looking for a Data Scientist who will support our Risk and Technology teams with insights gained from analyzing company data. The ideal candidate is adept at using large data sets to find opportunities for product and process optimization and using models to test the effectiveness of different courses of action. They must have strong experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms and creating/running simulations. They must have a proven ability to drive business results with their data-based insights. They must be comfortable working with a wide range of stakeholders and functional teams. The right candidate will have a passion for discovering solutions hidden in large data sets and working with stakeholders to improve business outcomes.

Primary Responsibilities

    Designs, develops and programs methods, processes, and systems to consolidate and analyze unstructured, diverse “big data” sources to generate actionable insights and solutions for client services and product enhancement.

    Analyzes complex business problems and issues using data from internal and external sources to provide insight to decision-makers.

    Identifies and interprets trends and patterns in datasets to locate influences.

    Constructs forecasts, recommendations and strategic/tactical plans based on business data and market knowledge.

    Creates specifications for reports and analysis based on business needs and required or available data elements.

    May provide consultation to users and lead cross-functional teams to address business issues.

    May directly produce datasets and reports for analysis using system reporting tools.

    Uses advanced mathematical and statistical concepts and theories to analyze and collect data and construct solutions to business problems.

    Performs complex statistical analysis on experimental or business data to validate and quantify trends or patterns identified by business analysts.

    Constructs predictive models, algorithms and probability engines to support data analysis or product functions; verifies model and algorithm effectiveness based on real-world results.

    Designs experiments and methodologies to generate and collect data for business use.

    Projects may include a focus on “quantitative finance” or help identify new business opportunities.


    We’re looking for someone with 5-7 years of experience manipulating data sets and building statistical models, and has a Master’s or PHD in Statistics, Mathematics, Computer Science or another quantitative field.

    Knowledge and experience in statistical and data mining techniques

    Strong problem solving skills with an emphasis on product development.

    Experience using statistical computer languages (R, Python, SLQ, etc.) to manipulate data and draw insights from large data sets.

    Experience working with and creating data architectures.

    Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks.

    Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with applications.

    Excellent written and verbal communication skills for coordinating across teams.

    A drive to learn and master new technologies and techniques.

    Experience querying databases and using statistical computer languages: R, Python, SLQ, etc.