software research and engineering | Palo Alto, CA
PhD in Computer Science or Statistics with 5 years experience with machine learning, statistical methods, knowledge representation, modeling and simulation in industrial applications.
PARC’s Intelligent Systems Lab is looking for a research scientist in machine learning to develop powerful methods for extracting meaningful patterns and trends from temporal, spatial and relational data.
Increasingly the edge in information services comes from being able gain actionable insights from data. Our work for Xerox Services as well as commercial and government clients requires analyzing large data sets with many unique and interesting challenges. In transportation, the data include urban and highway traffic flows, transaction data, parking occupancy, and activities in cities and urban and departments of transportation. In government services, the data relate to health and social services, prescriptions, transactions, and activities by healthcare providers, pharmacists, and government social services. . In healthcare, the data include hospital medical data relating to patient care, medical conditions, and activities in hospital, clinics, and home healthcare. Our focus is on the activities of organizations.
Recent projects include real-time contextual information for nurses in hospital, discovering groups of fraud conspirators in networks of pharmacies, doctors, and patients workflow support for mobile response organizations in cities, helping government agencies identify children whose foster parents are failing them, improving consumer health and reducing obesity using social networks data, networked parking resource management for cities, analyzing traffic camera images for defects, and detecting malicious insiders in organizations.
We look for opportunities to leverage big data, machine learning, organizational modeling, and analytics in helping organizations be evidence-based, and reflective in providing effective services. We work to provide analytics, context-specific information, and support for coordination to re-invent smart organizations.
- Perform large-scale data analysis and develop effective statistical and machine learning models for classification, optimization, clustering, time series analysis, spatial analysis and so on.
- Design and implement dashboards that track key business metrics, spot anomalies, and provide actionable insights.
- Use effective approaches for importing and integrating information from multiple sources into systems that model and analyze cities and other complex organizations.
- Track industry trends and use cutting edge technologies that help scale our team.
- Rapidly learn new domains and formalize problems.
- PhD in Computer Science, Statistics or related field or five years of equivalent experience.
- Ability to formalize practical industrial problems and an understanding of the practical considerations of analytics including data cleaning and the ability to creatively design data features to expose important aspects of a domain.
- Core knowledge of statistical methods, knowledge representation, modeling and simulation.
- Practical knowledge of machine learning techniques including both supervised and unsupervised models (extraction of patterns, density modeling, regression and classification for spatial, temporal and graphical data)
- A passion for problem-solving, comfort with ambiguity, and creativity.
- Ability to prototype practical industrial applications using common programming languages and toolkits.
- Ability to thrive in a dynamic and fast-paced environment and drive change and collaborate effectively with a variety of individuals and organizations and a multi-disciplinary team including specialists in user interface design, visual analytics, and simulation and modeling.
- Proficiency in main objected-oriented and script programming languages such as Java and Python.
- Experience with big data and large scale machine learning, ETL, and relevant toolkits, such as Hadoop HBase, Mahout, and Hive.
- Bayesian graphical models, Statistical Relational Models, Hidden Markov Models, Random Fields
- Experience with unstructured data analysis, especially geographic and linguistic data.
- Experience with WEKA, Orange, libsvm, Alchemy, SQL, pyml, R, JAGS, Matlab (stats & image processing)
- Anomaly detection, recommendation systems, pattern mining, trend prediction
We offer a very competitive salary package and full benefits (medical, dental, vision, life & disability insurance, 401K). PARC employees enjoy the use of onsite health & fitness center and collegial dining at our onsite cafeteria. The PARC campus is in a spacious modern building in close proximity to the resources and opportunities of Silicon Valley and benefits from nearby leading universities such as Stanford and Berkeley. It is also close to many amenities, top schools, and outdoor activities (seehttp://www.parc.com/about/culture.html). PARC provides a highly diverse environment and is proud to be an equal opportunity employer (see http://www.parc.com/about/careers/).
About the group
PARC’s Intelligent Systems Laboratory (ISL) research organization is unlike any other. Combine the best of an esteemed research group, a top-notch university, an entrepreneurial startup, and a premiere technology company and you get ISL. Our group melds its world-class innovation chops with researching and developing real-world applications that have market potential, focusing on creating new business options and opportunities. We’re driven to get our ideas out of the lab and into the world, and we need superb research talent to make that happen.
PARC, a Xerox company, is in the Business of Breakthroughs®. Practicing open innovation, we provide custom R&D services, technology, expertise, best practices, and intellectual property to Fortune 500 and Global 1000 companies, startups, and government agencies and partners. We create new business options, accelerate time to market, augment internal capabilities, and reduce risk for our clients.
Since its inception, PARC has pioneered many technology platforms – from the Ethernet and laser printing to the GUI and ubiquitous computing – and has enabled the creation of many industries. Incorporated as an independent, wholly owned subsidiary of Xerox in 2002, PARC today continues the research that enables breakthroughs for our clients' businesses.