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U-M Career Resources – Career Center
Redfin (real-estate firm) – Yong Huang (Head of Data Science; UM alum) is visiting campus on 6/23/2017 to meet with graduate students interested in a career in data science and machine learning. Yong’s team is responsible for delivering customer facing machine learning features like Redfin Estimate, Hot Home and Recommendations. Contact Yong at email@example.com to schedule a 1:1 meeting.
City of Detroit – Around the world, cities are bringing the practice of innovation into government as a way to address pressing urban challenges and improve the quality of life for residents. Recently, the City of Detroit was selected by Bloomberg Philanthropies to receive a grant to establish a dedicated Innovation Team. The City of Detroit’s cross-functional Innovation Team is housed within the Mayor’s Office and is charged with developing and implementing innovative solutions to the city’s most pressing challenges. Together, the Innovation Team will work with its partners in city government to disrupt the notion of what is possible, tap into new perspectives, and restlessly search for innovative solutions to the root causes of pressing urban problems.
The City is hiring a Senior Design Researcher, a Senior Data Scientist, and an Innovation Analyst. Full details and online applications for all three positions are available here. The postings will be live until June 11.
Swift Biosciences – This Ann Arbor company has 2 positions available (Long Read and NGS Analyst, respectively). Postings can be found here:https://swiftbiosci.com/careers/. If you have questions, contact Sushma Chaluvadi.
TD Ameritrade – The Ann Arbor office is looking for a Sr. Developer / Data Scientist. Resumes and questions can be sent to Sean Law. NOTE: applicants must be U.S. citizens or Permanent Residents.
abbvie – A biopharmaceutical company in Chicago is seeking a postdoc in computational genomics. Company details, job description, and online application link can be found here: https://abbvie.taleo.net/careersection/2/jobdetail.ftl?job=1703114&lang=en.
Columbus Technologies – The company is seeking a Bioinformatics Scientist to work with the NIH in Bethesda, MD. Applicants must have a Ph.D. and be U.S. citizens. Job details plus an online application link can be found here: https://careers.columbususa.com/job.php?id=1245. If you have questions, contact Mykeshia McNorton, Technical Project Manager.
Quicken Loans – Quicken Loans Careers
Data Scientist; requires a Master’s degree or above in computer science, statistics, applied mathematics, operations research, engineering, economics, social sciences or a similar field; strong benefits package, professional/ personal development; anti-corporate culture to build strong teams.
Agilent – Agilent Careers
Amway – Amway Careers
Columbia Business School – Columbia Business School Careers
Research Associate to assist faculty research with data analytics in Accounting; Decision, Risk & Operations (DRO); Marketing; and Management. For further information, visit http://www8.gsb.columbia.edu/faculty-research/research/job-opportunities/research-associate
Eaton – Eaton Careers
Data Science Specialist, requirements include a Master’s Degree and knowledge of machine learning and sensor fusion technologies applied to connected and intelligent vehicles.
Fidelity Life Insurance – Meggie von Haartman, firstname.lastname@example.org. Please reference that you are a MIDAS student and referred by Dr. Gopalan.
Marketing Data Scientist- Intelligent Customer Interactions: Job Posting 26977BR – Ford Motor Company’s Global Data, Insight, and Analytics (GDIA) organization is looking for motivated and talented individuals with a background in Data and Analytics to work on personalized marketing and customer engagement analytics problems. This is a dynamic and challenging opportunity to apply the latest tools and methods in Big Data and Data Science to a variety of business problems at Ford.
Gongos – Statistical Analyst position in Data Science unit, location Auburn Hills, MI
Google – Google Careers
IBM – IBM Careers
MassMutual Financial Group – MassMutual Financial Group Careers
Microsoft – Careers
The Microsoft Data & Decision Sciences Group is looking to hire a Principal Data Scientist to support projects that focus on Artificial Intelligence and Cognitive analytics. The team is looking for an expert in this field from business/academia with extensive experience in this area.
Nielsen – Nielsen Careers
Sphere – Sphere Careers
Lead Developer, Lead the development of Sphere algorithm and its connection with other parts of the Sphere platform.
Go Developer, Develop back-end algorithm in the Go language.
Swift Developer, Develop Sphere’s first iOS application in Swift.
Stanford University – Stanford Careers
Systems and Technology Research – STR Careers
Zilliant – Zilliant Careers
Continuing Training and Education
NEXT application period: December 1, 2017 – January 31, 2018 at 12 noon (Central European Time)
Program dates: The program will take place from July 2, 2018 to August 31, 2018
Insight Data Science Fellowship: An intensive 7-week Fellowship Training Program (tuition free) introducing academic trainees to practical data science industry applications and providing mentoring and networking support.
The DataIncubator Data Science Fellowship: Cornell University Data Incubator offers a free 8-week data science training partnering with high tech companies.
Ongoing Data Science Bootcamps: A variety of opportunities for hands-on team-based data science training.
2017 Wolfram Summer School – A unique educational and career opportunity to learn and do projects at the frontiers of science, technology, and innovation. Learn how to apply Wolfram’s unique approach to creating ideas and turning them into research, products, and companies.
Data Science Practicum Opportunities
“Deconvolving the Noisy Universe: a machine learning approach to analyze astronomical images”; 4 month project for students; mentor is Arya Farahi, PhD Student; the team will use a machine learning approach to analyze astronomical images; affiliation is the U-M, Department of Physics.
“Machine Learning Models for an Automated Data Science Pipeline” – Professors Laura Balzano and Jason Corso are offering this practicum opportunity. This is an effort to develop machine learning modules that can be incorporated into a data science pipeline supported by DARPA. There are 10 data science problems including tabular, text, audio, and image data. All programming will be done in Python. Please contact Laura(email@example.com) or Jason(firstname.lastname@example.org) if you are interested.
Michigan Sports Analytics Society: The Michigan Sports Analytics Society exists to develop a platform for students to collaborate, gain experience, and publish high-level work in the field of Sports Analytics. This is an opportunity for research experience and mentoring that could be counted as Data Science Practicum.
Baseball – Soon, the University of Michigan’s baseball team will be getting a system called “TrackMan” installed in to their stadium. This is a system that exists in all MLB stadiums and is used to produce a lot of the stats on StatCast. With relation to hitting, these stats include exit velocity, launch angle, direction, hang time, spin rate. Basically, after a hitter hits a pitch, we can see what speed it came off the bat, what angle it came off at, what direction it went, how long it stayed in the air, and how fast it was spinning after it was hit. Conversely, we can see all of this for a pitcher as well. We can see velocity, spin rate, amount of break/curve. Along with this, we can see the angle of the pitcher’s arm, the pitcher’s extension, and other various factors related to the biomechanics of the pitcher himself. Athletics is interested in all of these because they can validate hitters in slumps vs hitters who are just getting unlucky. Also, they are very interested in monitoring their pitchers. More importantly, they just want to be innovative with their analytics and become one step ahead of the game. What our baseball research team has formulated is a plan to follow once the trackman system gets in. This plan included understanding of the parameters before they come in, and preliminary ideas to get started as soon installation is complete.
Basketball – The University of Michigan’s Men’s and Women’s basketball teams are using wearable devices from a company called Catapult to produce information on their players. Largely, the device is able to capture various metrics of the player using the movements of that specific player. Thus far, it has been used to monitor a player over-working or under-working which can possibly lead to injury. Athletics is definitely interested in using it to predict injuries or determine why an injury occurred. Although it would take a lot of time to determine anything significant because there are so few injuries in a season, what we have already done is provided athletics a good basis for what has taken place with the catapult device and how it relates to injuries. This project team was able to investigate the acute/chronic ratio with relation to injuries. They were also able to build a simple calculator for a coach to enter time and drill name, and it would let them know what the expected output of the wearable device. Now what we can do next is to connect the wearable devices to in-game performance and really figure out the best practice schedules to create better player performance and hopefully lead to wins!
Soccer – The University of Michigan’s Men’s and Women’s soccer teams are using wearable devices from a company called Catapult, to produce information on their players. Since soccer is an outdoor-field sport with few stoppages, the Catapult device is very valuable because the data is going to be much more condensed in terms of consistent activity being produced. What our soccer research team has investigated is the variety of injuries that are occurring and how they relate to what the catapult device is telling us about certain players. We have been able to check for imbalances in players, and even attempted to build a classifier that could tell us when a player may get hurt. With more help, we could transition to providing live analysis during practices and games that can be fed to coaches and trainers. We would also be able to match up Catapult outputs to team performance stats such as time of possession and shots on goal.