HopHR is an online marketplace for hiring top data science talent.
Our approach is different for a reason:
We are unlocking insights you won’t find elsewhere, so you can make the best decisions that lead to the right job fit.
Our candidates complete a 2-week mentorship program with an experienced Data Scientist. Each candidate’s technical skills and thought processes are assessed and a detailed report is included on his or her online profile.
At the end of each mentorship cycle, we release our candidate profiles and assessment reports to our partner companies. Hiring Managers can then send interview requests, schedule interviews, and send job offers through our platform. It couldn’t be easier!
Our mentors are handpicked for their depth of experience and their passion for mentoring.
Diana is Chief Data Scientist, Financial Services Sector, Industry Solutions at IBM. Her focus is mainly on client insights for wealth managers and retail banking. One of the new solutions Diane is currently working on is RCA (Regulatory Compliance Analytics), a cloud-based solution that reads and interprets banking regulations by leveraging IBM's Watson APIs.
Data Scientist at Airbnb, work on the paid growth team which is a marketing group that is charged with growing our user base. I build models to predict customer lifetime value, churn, and other things that are related to marketing.
I use a wide array of tools but some of my favorites are sklearn, vowpal wabbit, DataRobot, xgboost, H2o, and recently Spark.
Mr. Givre is a Senior Lead Data Scientist at Booz Allen Hamilton. He is passionate about teaching others how to use data to its fullest. At Booz Allen, Mr. Givre has been instrumental in developing data science and analytic training programs which have expanded the use of data science throughout the firm. He is a regular speaker at international data science conferences such as Strata +Hadoop World, Open Data Science Conference, and others. Mr. Givre is a contributor to the Apache Drill project and is currently working on a book about it for O'Reilly publishing. He holds a Masters Degree from Brandeis University and two Bachelor's Degrees from the University of Arizona. Mr. Givre's blogs at thedataist.com.
Mehdi Salmani Jelodar joined SanDisk Corp’s big data team as Sr. Data Scientist. He works on developing algorithms and tools using machine learning and large-scale data to improve flash memory technology development procedure in different areas. Mehdi obtained his Ph.D. degree in electrical and computer engineering at Purdue University. His doctoral studies were in the field of computational nanoelectronics. He conducted research to predict and optimize the effects of novel materials and geometries in ultra-scaled transistors for future technologies and has published more than 30 papers, posters and presentations.
Dara finished her Ph.D. in computational immunology at Stanford in early 2016. She then became a Data Scientist at Collective Health, where she works on fraud detection models, data pipelines, and expert systems for healthcare data.
Data Scientist formerly @LinkedIn. Entrenched in Data Science culture. Specialist in Recommender Systems & Email/'Inbox SEO'
Currently operating a small data science consultancy that works with startups.
Ashkan Jafarpour is currently a Research Scientist at Yahoo. He received his Ph.D. in Electrical Engineering at UCSD. Before arriving at UCSD, Ashkan completed his BSC at Sharif University of Technology. His skills are mainly in Algorithms, Statistics, Machine Learning and Data Scientist.
After a Ph.D. in Theoretical Physics and a postdoc in Computational Biochemistry, Shoresh realized he is more excited about the challenges in the industry. To find what positions fit his skills the best, he spend long hours talking to people, attending networking events, reading books and articles, and learning new skills. Currently, he is a data scientist in a well-established startup in financial technology.
Amir is a Data Scientist at Hart where he builds data products backed by Machine Learning that engages millions of patients with their health and fitness. Previously he worked at Compellon, a scalable Machine Learning as a service company, where he helped Fortune 500, as well as startup companies to build intelligent applications. He holds a master's degree in data science from UC Berkeley.
Moein obtained his Ph.D. in Industrial Engineering from Arizona State University with a research topic in designing the experiments for functional responses data and GLMs. Moein joined PayPal as a data scientist in May 2016. Prior to joining Paypal, he worked as a data scientist at Discover Financial Services for about 2 years, supporting several teams such as AML and fraud modeling.
Before joining Airbnb as a lead Natural Language Processing (NLP) and Machine Learning (ML) data scientist, Yashar was a Research Scientist Manager at Yahoo Labs. He also collaborated with a few startups as a consultant in the areas of NLP and ML.
Yashar has published more than 40 scientific publications with about 600 citations and also filed 10 patents. He also served as a chair, co-organizer, program committee and reviewer in various top-tier academic workshops, conferences, and journals.
Yashar holds a Ph.D. in the field of Machine Learning and Natural Language Processing from the University of Trento.
Mohsen is a senior business analyst at Sears Holding Inc. He received his Ph.D. and master's degrees in business analysts from Foster school of business, University of Washington and his bachelor's degree in industrial engineering from Sharif University of Tech. His background is in statistics, statistical modeling, machine learning and optimization. He believes an outstanding data scientist needs to master the ability to transform data into insight and insight into service, along with quantitative and programming skills.
Mehdi's research and work is in the intersection of model predictive control, optimization and machine learning, aimed at design, automation and optimal performance of large-scale, intelligent cyber-physical systems. In particular, he is interested in how a systems approach combined with learning from aggregation of large volumes of operational data can be used to solve complex large-scale problems, resulting in systems and machines with greater autonomy and intelligence.
Anirban Ghosh is a Machine Learning Scientist at Nokia Global R&D, where he is working for Nokia's Broadband and Networking products and especially on the enhancement of Nokia's existing product lines through scalable Analytic/Machine Learning solutions. Prior to Nokia, Anirban has been part of organizations e.g. Genpact, Target, and Wipro. He is having around 10 years of experience spanning over various sectors e.g. Retail, Telecom, Travel/Hospitality and various analytics support-lines, e.g. Marketing, Pricing, Customer etc. He holds bachelor's in Statistics from St. Xavier's College, Calcutta, and a master's in Applied Statistics & Computing from IIT, Bombay.
Abdel has 15 years of experience in various aspects of industry leading software organizations - focusing on solving complex large-scale data problems providing not only architectural direction but also the hands-on implementation of these systems. His current technical interests include reactive programming, IOT, Cloud Infrastructure, Distributed Systems Robustness, Blockchain distributed Identity management, Machine Learning, Apache Spark, Apache Mesos, Big Data, TensorFlow and Graph databases.
Nima is an entrepreneur and an enthusiastic data scientist and data architect. He has extensive experience on a good variety of data sets from neuro and bio data to social, retail and financial data. He studies common characteristics behind various complex networks and has developed an eye to see them. Nima is very passionate about visualization and telling stories with data. He is more focused on the use of big data analytics, statistics and machine learning for drawing business insights (BI), improve user experience and design of products.