Machine Learning Engineer
factspanSeattle (WA)
About the role
Factspan is a pure play analytics company. We partner with you to build an analytics center of excellence, generating insights and solutions from your data to solve business challenges, make strategic recommendations and implement new processes that help you succeed. With offices in Seattle, USA and Bangalore, India; we use a global delivery model to service our clients. Our clients include Fortune 500 companies in Retail, Financial Services, Hospitality and Technology sectors.
Job Description:
- Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed.
- Conduct end-to-end analysis that includes data gathering from various data storage platforms and requirements specification, processing, analysis, ongoing deliverables, and presentations.
- Hands on expertise in Machine Learning models using R/Python, SQL, well versed in statistical methodology including deep expertise and experience with statistical data analysis
- Requires a diversified technical person who can setup environments on AWS and integrate different pieces of solution.
- Develop data pipelines to integrate different data sources
- Experienced in using Google, Amazon NLP APIs to parse data and analyse output
- Experienced in using Amazon dockers to develop and deploy the solution
- Proficient in JAVA & Python programming
- Understanding of topic modelling, supervised & unsupervised machine learning
- Plan the project milestones, resourcing and work distribution
- Execute project in a timely manager, analyse risks and mitigate them
- Able to lead a technical team of data scientist and engineers
- Communicate the project progress, challenges, results and next action items to stake holders
Qualifications:
3-8 years of experience Bachelor’s/Master’s Degree in Engineering, Statistics, Mathematics Excellent hands-on working knowledge in R, Python, advanced predictive modelling, SQL, AWSAll your information will be kept confidential according to EEO guidelines.
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