Senior Principal Data Science Engineer

Join us as a Senior Principal Data Science Engineer.  This will be a US Remote position.

 How you’ll make an impact

Are you looking for a one-of-a-kind opportunity and ready to work on world-changing technologies? Are you passionate about analytics and knowledgeable about the supporting platforms that enable analytic solutions? How about building the next generation of the industry’s #1 Integration Platform as a Service? At Boomi, our vision is to harness the power of metadata by capturing the relationships and behaviors of applications and their interactions to reimagine and reinvent the customer experience. 
 
We are looking for data scientists to drive machine learning, NLP, data mining, and statistical modeling for predictive and prescriptive enterprise analytics, and to join a talented, fast-growing team. Successful candidates will be expected to understand data preparation needs and investigate the state of the art techniques in advanced machine learning and statistical modeling, and also design, develop, and deploy state-of-the-art, scalable systems for innovative analytics applications. Applicants will be expected to work with a diverse, large set of data sources to find opportunities for product and process optimization and use models to test the effectiveness of different courses of action. They must have experience using a variety of data mining/data analysis methods, using a variety of data tools, building and implementing models, using/creating algorithms, and creating/running simulations. They must have a proven ability to drive business results with their data-based insights.

Team Environment

Our team is collaborative, geographically distributed and enjoys working with each other, and we are eager to help each other succeed. We are self-starters with technical curiosity and a willingness to learn. We are open to sharing new ideas and improvements. We work on cutting-edge technologies to provide the best experience for the customer. We take pride in our work. If this sounds like you, then you may be a good candidate for our team!
 
What you’ll do

• Research, design, prototype, and deliver robust and scalable models based on machine learning, data mining, and statistical modeling to answer key business problems, improve the product, increase and optimize customer experiences, and other business outcomes
• Develop and implement NLP techniques such as sentiment analysis, entity recognition, topic modeling, and summarization to extract insights from unstructured data.
• Build cost-effective tools and support structures needed to analyze data, perform elements of data cleaning, feature selection, and feature engineering and organize experiments in conjunction with best practices
• Work with development teams & business groups to ensure models can be implemented as part of a delivered solution across many clients
• Present findings to stakeholders to drive improvements and solutions from concept through to delivery
• Keep abreast of the latest developments in the field by continuous learning and proactively champion promising new methods relevant to the problems at hand
• Collaborate closely with other scientists and engineers in a multidisciplinary work environment
• Prepare reports for executive leadership that effectively communicate trends, patterns, and predictions using relevant data.
• Apply for patents/innovation disclosures
• Publish and present our work at relevant tech/industry conferences

What you’ll need to succeed in this role

• Total experience of 10+ years
• Bachelors in computer science or a related field with 5+ years of experience in building data science models, data modeling, and business intelligence.
• 2 or more years of leading data science teams
• Deep knowledge of fundamentals of machine learning, NLP, data mining, and statistical predictive modeling, and extensive experience applying these methods to real-world problems
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world applications, advantages/drawbacks
• Strong skills in software prototyping and engineering with expertise in applicable programming and analytics languages (Python, SQL) and various open-source machine learning and analytics packages to generate deliverable modules and prototype demonstrations of their work
• Experience in entire model lifecycle development, debugging, and deployment using PyTorch, Tensorflow, OpenAI and other relevant tools and technologies.
• Strong problem-solving skills with an emphasis on product development.
• Experience with various AWS services like Amazon SageMaker, Amazon EMR, Amazon S3, and Amazon Lambda is a huge plus.
• Experience using continuous integration and deployment (CI/CD) processes for ML models using AWS CodePipeline, AWS CodeCommit, and AWS CodeDeploy.
• Implement best practices for monitoring, logging, and alerting of ML models using AWS CloudWatch, AWS X-Ray, and other relevant tools.
• Mentor junior data scientists

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