Data Scientist - Product Insights

We are a series-A startup building perception systems for autonomy. We are based in the San Francisco Bay Area, funded by NEA (https://www.nea.com/), and our core team includes faculty entrepreneurs (Stanford and UC Santa Barbara) and industry veterans (Uber, Apple, Amazon Lab126, Rohde & Schwarz), who have successfully shepherded signal processing and machine learning innovations to large-scale software for location improvement and safety at Uber, led the development of state-of-the-art computer vision technologies that shipped over millions of Amazon devices, and delivered zero-to-one product experiences at Uber and Box. Our core product grew out of 5+ years of university R&D by our co-founders. You can find out more about us by visiting our website (https://www.plato.systems/) and our notion page (https://plato-systems.notion.site/Meet-Plato-Systems-82230c5f8b8e44f2ac12e7cdf65a0ad5).Our mission and team expertise spans beyond software to advanced sensor systems, algorithms, embedded systems, signal processing, and machine learning. Our team is building and deploying edge software and cloud services for real-time customer facing products as well as internal big data tools. We look for people with a depth of expertise and experience in one of these areas, and with the intellectual curiosity for interacting with, learning from, and teaching world-class experts in areas outside their expertise.We currently have a full-time opportunity as a mid-level Data Scientist at Plato Systems. In this role, you will work closely with our data scientists, engineering team, and Product Management, & work collaboratively with them to transform data generated by our fleet of edge devices into data products that provide actionable insights to our end customers. A successful candidate for this role will be someone who can understand business needs, excels at exploratory data analysis, can discover and generate insights from the data, and create visualizations and dashboards that inform both internal product team as well as our end customers.Responsibilities

Perform exploratory data analysis, generate and discover actionable insights from Plato's unique spatio-temporal data, conduct hypothesis testing, and utilize statistical methods to assess their validity.Work closely with Plato's product managers, understand the context of the KPIs & customers' business needs (as opposed to what they ask for) in order to help create products or experiences that address customer pain points.Strive to become an internal expert and consultant for each customer insight moduleRapidly generate and iterate through hypotheses to build relevant, story-driven insightsTell compelling stories that use the data – and data visualization - to compel the audience with the power of the insightWork in a data-driven environment, drive process improvement, and work with the stakeholders to translate high-level business goals to working software solutions and customer-facing outputs.“Own” your work – take initiative, be proactive, ask questions to bring clarity, share ideas and challenge the norm, anticipate and complete projects in a comprehensive manner.Required Qualifications

Bachelor's, Master's, or above in engineering, applied science, or a related quantitative field such as economics.3+ years demonstrated experience in working on data products, exploratory data analysis, and generating actionable insightsSelf-starter, methodical, high-velocity, motivated, responsible, innovative and technology-driven person who performs well both solo and as a team memberA proactive problem solver that has great communications skills to relay findings and solutions across technical and non-technical audiencesPreferred Qualifications

Experience with one or more of time-series analysis, statistical analysis, anomaly detection, regression, clustering, and computer vision fundamentalsPhenomenal data visualization and analysis skills with expertise in Looker, Tableau, Power BI, Seaborne, etc.Ability to understand large data sets and use appropriate technologies and methodology to manipulate data (e.g. SQL, R, Python, ETL pipelines)Prior experience with modern data technologies stack such as Databricks, Airflow, etc.Strong written and verbal communication skills

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