Data Scientist - Multiple Levels (TS/SCI with Poly Required)
Red AlphaAbout the role
A little about us:
Culturally, it probably suffices to say that we take our work seriously, but not ourselves. Our leaders have spent time in the trenches and have cursed daylight savings time changes and trailing whitespace as many times as you have. We like to say that we spend 80% of our time cleaning the data...and 20% of our time complaining about cleaning the data. Joking aside, our voices matter, and it is easy to see how our decisions affect the Data Science practice and Red Alpha as a whole. We have a clear vision of where we are headed.
Our team takes a pragmatic approach to Data Science, defining it loosely as the intersection of technical expertise, business acumen, and soft skills to solve business problems with data. We spend a lot of time trying to understand the problem before we set about building a solution, and we prefer lower tech useful solutions over shiny algorithms and dust on the shelf. Did we mention we’re pragmatic? We have a diverse set of skills across our team, and whether you are a traditional Data Scientist (whatever that means…), an Applied Research Mathematician, a Database Engineer, a Full Stack Developer, or something else in that neighborhood, if you have a knack for picking apart data to make sense of it, we would enjoy having a conversation with you.A day in the life:
- Enabling and growing existing automation efforts, adding additional data streams, and driving forward data transformation efforts.
- Focusing on the sponsor’s business analytics, metrics collection, and analysis efforts. The sponsor’s management team requires a data scientist to characterize the sponsor’s workforce, workforce productivity and output, and the value of collection to the workforce.
- Possessing an instinctive aptitude to leverage information and knowledge sharing networks and navigate conflict in a way that fosters constructive outcomes.
What you bring to the table:
All of our data scientists need the following skills:
- Proficiency with a scripting language such as R or Python
- Experience with data science techniques and algorithms such as classification, clustering, random forests, deterministic forests (jk), hierarchical modeling, deep learning, Markov Chain Monte Carlo, and others. Note that you do not need to have all of these (we hope you enjoyed our random smattering of techniques…!) but you should be comfortable and capable with several of them and know some others not on this list.
- A B.S. Degree in Data Science, Mathematics, Computer Science or related field.
- For entry-level data scientists, 0-3 years of experience on Data Science projects.
- For mid-level data scientists, 3-6 years of experience on Data Science projects.
- For senior-level data scientists, at least 6 years of experience on Data Science projects with at least 3 years of experience managing teams.
- A TS/SCI with Polygraph security clearance.
For this particular role, you will also need:
- A broad range of knowledge including information techn
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