Senior Principal Data Scientist at Splunk

About Splunk:
Join us as we pursue our disruptive new vision to make machine data accessible, usable and valuable to everyone. We are a company filled with people who are passionate about our product and seek to deliver the best experience for our customers. At Splunk, we’re committed to our work, customers, having fun and most importantly to each other’s success. Learn more about Splunk careers and how you can become a part of our journey!
As part of Splunk’s R&D organization, the Data Science Team is passionate about providing quantitative analytics and evidence to inform business decisions. We focus on developing deep, quantitative understanding of how customers buy, use and adopt Splunk products and services. We partner with cross-functional business stakeholders to identify and address critical business questions and use data, analytical methods, and modeling to translate quantitative assessments into actionable insights. Rigorous data science research and analyses inform business challenges such as guiding product roadmaps, streamlining engineering development lifecycles, and accelerating customer adoption and utilization trends. We are seeking a Senior Principal Data Scientist who is passionate about framing and solving practical business questions with rigorous, quantitative data science approaches.
Role:
As a Senior Principal Data Scientist, you will partner with Splunk leaders to articulate crisp business questions and develop the architecture and methodologies needed to execute quantitative assessments and analytics that provide context and evidence to answer these questions. This will encompass creating a collaborative environment with other scientists and engineers to use rigorous quantitative research methods and data presentation to uncover the factors that drive business solutions. You will help architect and build the analytical experiments, models, reports, and dashboards and translate quantitative assessments into actionable insights.
Responsibilities:
Serve as a go-to technical resource for other data scientists. Structure and build analytical experiments, models, reports, and dashboards using statistical and other quantitative analytical methods.Model technical excellence across the end-to-end data science life cycle. Lead technical reviews and set the bar for excellence in data science projects across the organization.Model and mentor others in structuring business questions, developing work statements, and documenting and delivering analysis plans in tangible, practical, and clear prose & presentation forms.Lead investigator in analysis projects. Serve as the technical guide and direct the work of other data scientists and analysts. Deliver results in clear prose & presentation forms.Ensure rigor in underlying methods to retrieve, condition, validate, synthesize, and manipulate data.Create order from chaos - provide structured solutions for ambiguous problems Translate metrics and analytics into digestible products that inform business decisionsIterate, document, and communicate throughout problem lifecycle. Serve as a model resource for excellence in data science delivery.
Requirements:
Passion for framing and solving practical data-driven business questionsSelf-starter with a demonstrated track record of critical thinking translated into concrete products.Demonstrated ability to work across executive-level business stakeholders.Demonstrated track record of transforming ill-defined requirements into structured data science problems, serving as a technical leader for selecting and structuring scientifically rigorous methods, and breaking down large and complex problems that engage other engineers & scientists.Agility manipulating, synthesizing, and interpreting large and diverse datasets.Deep software engineering skills in an interpreted language. Ability to lead technical data science method and code reviews. Deep experience with statistical methods and software packages.MS or PhD in Computer Science, Statistics, Applied Math, Physics, Engineering or other technical field preferred or equivalent practical experience12+ years of professional experience in quantitative analysis, research, data science or engineering (statistics, applied math, inference, predictive methods, uncertainty quantification, design of experiments, etc.) including project leadership.Demonstrated written and verbal communication, collaboration, and mentoring skills.Strong analytic storytelling skills.
We value diversity at our company. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or any other applicable legally protected characteristics in the location in which the candidate is applying.
For job positions in San Francisco, CA, and other locations where required, we will consider for employment qualified applicants with arrest and conviction records.