Senior Scientist - Machine Learning & Probabilistic Modeling

Job Title: 
Senior Scientist - Machine Learning & Probabilistic Modeling
Job Type: 
Full Time
Location: 
Cambridge, MA
Qualifications/Job Description: 

This is an exciting opportunity for an enthusiastic computer scientist with strong expertise in artificial intelligence, probabilistic modeling, and machine learning, to work on cutting-edge intelligent systems research applied to real-world challenges.

Example projects you would work on include:

Detecting emerging medical conditions based on data collected from cellphones
Predicting and monitoring faults in microgrid power systems
Recognizing workflows from streaming activity data
Modeling patterns of network attacks and defenses
At Charles River Analytics, you will develop and use ideas from a number of fields including probabilistic modeling, machine learning, programming languages, natural language understanding, and cyber security. You will work in tightly-knit, small project-oriented teams with a Principal Investigator and other scientists and software engineers to create software prototypes of new research concepts. You will have the opportunity to design and execute your own research projects, growing into a Principal Investigator where you will pursue your own interests. You will also have the opportunity to attend conferences and have your work published.

Major Responsibilities/Activities:

Design new methods or use existing methods from the literature to solve problems for challenging applications
Write papers and reports on existing projects
Formulate new ideas and develop proposals for new projects, including establishing new areas of research
Present your work to customers, collaborators, and the research community
Communicate effectively with supervisor and other team members

Minimum Requirements:

PhD degree in Computer Science, Engineering, Mathematics or a related field
Expertise in probabilistic modeling and machine learning methods
Demonstrated ability to regularly develop new methods/approaches to create novel contributions to the state of the art
Ability to work independently or within a team environment
Ability to translate user needs and system features into actionable requirements for software engineering teams to produce technical solutions
US Citizenship

Preferred Requirements:

Knowledge of probabilistic programming
Experience with system modeling and prediction
Demonstrated experience building artificial intelligence applications in a general purpose programming language such as Java, Scala, and/or Python.
Experience directly interacting with customers and/or users
Proven ability to generate proposals, publications, or similar written materials

Benefits:

Charles River Analytics offers competitive compensation plus bonus and profit-sharing, with an attractive benefits package including: up to 92% employer-paid medical and 100% employer-paid dental, vision, life and disability insurance, paid maternity/paternity leave, tuition reimbursement, monthly gym allowance, free parking, generous paid time off, and a casual environment. We are also accessible by public transportation.
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Charles River Analytics is an equal opportunity employer and all qualified applicants will receive consideration for employment without regard to race, color, religious creed, national origin, sex, sexual orientation, military service, veteran status, age, ancestry, genetic information, gender identity and expression or disability.

Charles River Analytics is an Affirmative Action Employer and complies with the Americans with Disabilities Act Amendment Act (ADAAA). If you have a disability and would like to request an accommodation in order to apply for a position at Charles River Analytics, please indicate so on your application.

Company Name: 
Charles River Analytics
How To Apply: 
Please apply here: https://www.cra.com/careers/job-listings?gh_jid=1160450
Contact Name: 
Amanda Florentine
Start Date: 
Wednesday, December 19, 2018
Should this position be emailed to the job opportunities mailing list?: 
Yes