Senior Data Science Engineer
We are a collaborative, driven, get-it-done engineering team who love dealing with large amounts of data and solving hard problems. It’s time to start taking advantage of all the data we ingest and start revealing insights quickly and at scale, and we’re looking for an experienced Data Science Engineer who will bring a scientific mindset, a passion for data, and a commitment to engineering excellence. You’ll work with a variety of modern web, cloud, big data, analytics, and integration technologies. As a hands-on data science engineer, you will be responsible for building production quality analytics features into the product, working with customers to answer hard questions from their data and presenting the results as and when needed. You will shape the future of our data science efforts in the company and have a lasting impact on our customers, team, and industry.
If you love Data science, Machine learning and AI, building high quality analytical products, partnering with customer success, product and marketing to build products that delight customers and reveal great insights — this is the role for you.
- Build and test analytic and statistical models to improve a wide variety of both internal data-driven processes for unsupervised single-channel analytics, mapping and external customer-facing journey specific modeling needs.
- Work closely with existing Data Scientist and Product teams in Seattle.
- Function as a modeling expert on internal and customer-facing external projects. Will need to work with a group of customer success and data engineers on a project
- Help deploy and productize Usermind's predictive analytics products/systems and predictive model deployment framework like PMML/OpenScoring.
- Design and analyze framework for A/B experimentation using Usermind's journey orchestration engine.
- Act as an expert and evangelist in areas of data mining, machine learning and deep learning, statistics, and predictive analysis and modeling.
- Masters or PhD in a discipline such as Statistics, Applied Mathematics, Computer Science, Econometrics, etc.with an emphasis on or thesis work in one or more of the following areas: computational statistics/science/engineering, data mining, machine learning, or optimization.
- Knowledge of data mining and analytic methods such as deep learning, regression, classifiers, clustering, association rules, decision trees, Bayesian network analysis, etc. Should have expert-level knowledge and experience in one or more of these areas.
- Proficiency with a statistical analysis package and associated scripting language such as Python, R, Matlab, SAS, etc.
- Programming experience with SQL, shell script, Python, etc.
- Experience with and demonstrated capability to effectively interact with both internal and external customer executives, technical and non-technical to explain the uses and value of predictive systems and techniques.
- Demonstrated proficiency with understanding, specifying and explaining predictive modeling solutions and organizing teams of other data scientists and engineers to execute projects delivering those solutions.
Nice to Have
- Minimum of 10 years related professional experience.
- Knowledge of and experience with tools such as Hive, SparkSQL, etc. for working with big data in AWS and/or Hadoop or Spark for data extraction and data prep for analysis.
- Experience in software development life cycle including coding standards, code reviews, continuous integration, testing, deployment and operational support, particularly of predictive analytics solutions and/or products.
- Experience working in an agile program management environment.