Company Description

Tamr is the enterprise data mastering company trusted by large enterprises like Blackstone, the US Air Force, Toyota, and GSK. The companys patented software platform uses machine learning supplemented with human feedback to master and prepare data across myriad silos to deliver previously unavailable business-changing insights. With a co-founding team led by Andy Palmer (founding CEO of Vertica) and Mike Stonebraker (Turing Award winner) and backed by top-tier investors such as NEA and GV, Tamr is transforming how companies get value from their data.

Job Description

Tamr field engineers are highly technical data scientists and engineers who understand all aspects of the business. We know how to pitch the product to anyone from software architects to business executives. Often were working on the most challenging problems in the enterprise and we have to dig deep to understand the business value and deliver technical solutions. As the companys outward-facing, technical resource, the work of the whole group is varied. We build prototypes, direct product development, work with sales on accounts, implement pilot solutions, and deploy full production rollouts. Field engineers are expected to be highly efficient and resourceful when leading these projects.

Qualifications

We are looking for someone who loves to write code, and has a genuine interest in being customer-facing. We are building and selling a human-in-the-loop machine learning platform for the enterprise to help companies automatically unify and categorize their data to drive new analytic insight. We are looking for engineers interested in creating front line code to solve real customer problems, ranging from back-end data processing and machine learning, to front end presentation and dashboarding.

Challenges that make this job interesting:

• The problem were solving is hard - enterprise data is messy and there is a lot of it. Its our job to derive value from this data in a flexible and scalable way
• Every customer is different - while there are similar use cases that we see repeatedly, every account presents new challenges and we need to be able to adapt quickly to each new situation

This job might be a good fit for you if:

• You have strong data science and/or software engineering experience
• You are excited about working for a startup and being a key contributor
• You enjoy working with customers and have excellent interpersonal skills
• You have machine learning knowledge/experience

Qualifications:

• BS, MS or PhD degree in Computer Science, Physics, Mathematics or similarly quantitative/technical field
• Polyglot programmer, with experience using technologies such as Python, Java, R, SQL
• Willingness and ability to travel to client locations on occasion
• Candidates for this position must be a U.S. Citizen. Please note if you have a security clearance (or if you have held one in the past).

Other Preferred Qualifications / Nice to Have:

• Deep understanding of data integration and transformation patterns such as messaging, ETL
• Hands-on experience with large distributed systems from an architecture and development perspective
• Hands-on experience with traditional data warehouse technologies and BI or visualization tools
• Machine learning knowledge/experience
• Front end software development expertise.  JS in particular
• Experience building enterprise applications, including integration with COTS systems
• Experience with any of the following technologies: Hadoop, Spark, ElasticSearch, Java, AWS
• DevOps and/or cloud solutions deployment experience a plus
• Advanced quantitative technical degree (MS or PhD) preferred

Additional Information

This position is available in Cambridge MA.

Tamr provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, disability, genetic information, marital status, amnesty, or status as a covered veteran in accordance with applicable federal, state and local laws.