Full-Time Data Scientist @ Raytheon – Boston, MA
Are you passionate about data, applied statistics, programming and visualization? Do you enjoy working in collaborative and high energy environments? Are you the type of person that enjoys continuous learning and developing data experiments and products in your own time related to the areas you care about? If so, you may be interested in joining a new Advanced Analytics Solutions team at Raytheon Integrated Defense Systems (IDS) in the greater Boston area.
We seek an entrepreneurial data analyst capable of working across functional and business areas with minimal supervision in order to support the application of data science methods and statistical techniques to data for internal use at Raytheon. You will work directly with the Manager of Advanced Analytics at IDS to develop and execute analytics products for internal business users. Solutions will span manufacturing, engineering, business development, supply chain, and quality control functions.
At Raytheon, we work together as one global team creating trusted, innovative solutions to make the world a safer place. Our innovation spans all domains: from land and sea to air, space and cyberspace. We’re inspired by a noble mission that’s shared by Raytheon employees around the globe and an inclusive culture that empowers employees and celebrates their contributions.
We seek a team player passionate about using data and emerging technologies to improve business outcomes. Do you have what it takes to excel as a Data Scientist on our Advanced Analytics team?
Relocation support is available at a capped budget to be discussed with the applicant of choice at the proper time, if the person is eligible per company policy.
US Citizenship is required in order to obtain a US Government Clearance when necessary to support specific programs in the future.
Once the selected applicant completes an initial transitional period for training and indoctrination, a “remote working schedule” will be an option for the selected applicant.
- Support Manager of Data Science in meeting with business stakeholders to identify and develop requirements for strategic use cases
- Collaborate with data owners and technology teams to source data sets required for analyses
- Apply quantitative techniques to cleanse and explore large, complex data sets in preparation for further analysis
- Apply data reduction, feature selection, and feature engineering techniques
- Develop and implement hypothesis tests
- Develop, validate, and operationalize appropriate mathematical and statistical algorithms and models, including implementation on large data sets
- Review, enhance, and execute operationalized algorithms and models
- Develop data products for and communicate analytic insights to internal stakeholders
- Effectively communicate statistical/mathematical techniques to non-technical audiences
- Create repeatable processes and scalable data products in collaboration with the advanced analytics team
- Stay current with new data science methods, technologies, industry trends and open source packages
- Attend events and conferences pertinent to the field and engage locally with extra-curricular data science and advanced analytics groups.
- US Citizenship is required in order to be able to obtain a US Govt. Secret Clearance as necessary for future projects that require it.
- Familiarity with self-service data preparation and workflow management tools such as Alteryx, Tamr, Paxdata, Trifacta etc.
- Experience with data visualization applications such as Tableau, RShiny, Plotly, Microsoft PowerBI, Qlik, Looker, SAP Lumira, etc.
- Experience with NoSQL and Apache stack data environments
- Familiarity with public cloud services such as AWS or Azure
- Self-starter with strong analytics, critical thinking, and problem solving skills
- Excellent communication skills, with ability to process and present complex information in a concise and compelling manner to non-technical audiences
- Ability and eagerness to learn and educate others
- Willingness to become strong in both Python and R statistical programming languages (not just one)
- Experience in diverse domains (manufacturing operations, supply chain, finance, engineering, information technology, business development, quality control)
Required Education (including Major):
- Bachelor’s or higher degree in Statistics, Econometrics, Engineering, Computer Science, Finance, Mathematics or a quantitative degree in other social science or hard science fields