Job Location: Washington County, OR
Join a high-performing, tight-knit team as a Data Scientist at a fast-growing company that is using the Internet of Things (IoT) to transform how organizations sense, monitor, and make decisions. Founded out of MIT in 2005, SmartSense is trusted by more than 2,000 organizations, including Walmart, SpaceX, Apple, CVS Health, Coca-Cola, and the US State Department to help them make sensor-driven decisions. We have a solution that our customers rely on every day to make mission critical decisions. We are looking for team-oriented change agents to help shape the future of IoT.
Members of the Data Services team are passionate about data products and, above all, advanced analytics that will delight our customers. We are inspired by data opportunities for prescriptive analytics and in building and delivering tools, infrastructure, frameworks that provide data insights, models, predictions, and prescriptions that increase the value of our data to our customers.
In this Data Scientist role, you will be a key hands-on contributor on the data services team. Our data science efforts will digest the entire breadth of our data topology from raw data ingestions to cold storage enabling our machine learning capabilities with training data from our vast repository of telemetry. As a data scientist you will discover new patterns, identify actionable insights and extract, qualify, and refine large data sets that enable customers decision making from our IoT platform data. You will be instrumental in delivering high value proprietary analytic capabilities to our customers.
This is an exciting opportunity for a Data Scientist ready to make an impact on this business by advancing data maturity with analytics at SmartSense creating predictive data products. Work with our team and envision a future of prescriptive analytics. Join us on our data journey today.
Core Technologies
R, SQL, Python, Git, ODBC, HTTP, AWS
Core Qualifications
- BS/MS/PhD in a scientific field or equivalent experience
- Fluent in two or more data programming languages; Python, R, Julia, Scala, Java, Go
- Demonstrable experience with SQL and proponent of Agile methodologies, particularly SCRUM
- Demonstrable data wrangling skills with big data and exploring new data sets for training models
- Demonstrable experience with regression, clustering, and classification algorithms
- Values code simplicity and performance and demonstrates an eagerness to learn
- Wants to work in a fast, high growth environment that respects its engineers and customers
- Familiarity with the core big data architectures, Data Lakes, Warehouses, streaming platforms, and machine learning.
Preferred Qualifications
- Demonstrable experience with Python and handling data contexts of Telemetry/IoT Data
- Expertise with Spark and/or Hadoop, NoSQL and Timeseries databases
- 4+ year’s working in the data science field, applying statistical data analysis to real-world problems
- 5+ years with data transformation and analysis tools and languages including SQL and Python
- 3+ years in data science in machine learnings solutions environment, preparing models, optimization techniques and applying them in pragmatic ways to solve business problems
Within 1 month, you’ll
- Complete onboarding with a tightly knit team solving hard problems the right way
- Meet the Product Team and learn the product roadmap for predictive analytics and other data products
- Become familiar with the topology of our data, data models, tools, and our access paradigms
- Build relationship with the awesome team members across other functional groups
- Participate in sprint planning and other project activities required by Agile software development methodology
- Become familiar, understand, and ask questions about our use cases for predictive analytics
Within 3 months, you’ll
- Proactively identifying and validating predictive analytics proposals that can be solved with ML
- Engage with the team to improve your understanding of our data commodities and relevancy towards the advanced analytic use cases such as real-time failure prediction.
- Identifying the convergence points for predictive opportunities in our streams and data flows and gaps in our technology/tooling which will facilitate our predictive analytics mission.
- Work all over the stack, moving fluidly between programming languages: Python, Scala, Java, Go, R, Julia, or more in pursuit of data set curation.
- Achieve mastery of the business domain around our data models and identifying data sets for modeling
- Proactively engaged with the team calibrating your experience, tool sets, outcomes to objectives
Within 6 months, you’ll
- Influence the architectural runway as applied to our product roadmap for advanced analytics
- Key in problem formulation, translating user stories into data science problems
- Participant in the design, implementation, testing of data products from our product pipeline for predictive models
- Challenge requirements while also having built confidence in story pointing with the mind to enhancing the quality and efficiency of our data products outcomes.
- Influencing technological solutions and the definition of new data sets for use cases defined by our product team for analytics
- Identify opportunities where SmartSense would benefit from applying data-driven decision making and applied ML techniques
- Key member in the R&D team facilitating the maturation of ML prototypes to productized models
Within 12 months, you’ll
- Assist the team in understanding the nature of our data to ensure quality and protect against data drift
- Influencing the product team on use cases complimentary to our advanced analytics product road map
- High impact on data strategies defining the needs of data science
- Understand data across customers and verticals, discover patterns and relations in the data, advance metric development, combine multiple data streams to better classify events
- Deliver on the identification of KPI with your models, experienced communication of methods to engineers for productization, optimizing the costs for generation of ML value
- Enable ML engineers to identify recurring problems in customer data
- Develop simulation models to classify different asset events so that SmartSense can deliver Real-Time event reporting and remediation plans.
- Key player in projects; breaking down the end-to-end analytics and data science into bite size chunks
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