Entry Level Algorithm Engineer Jobs in Washington

 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:

The Red Alpha Data Science practice grew out of Red Alpha's reputation in Software and System Engineering with our Department of Defense clients. As sometimes happens, customers who trust our expertise in adjacent areas asked Red Alpha to assist with some of their burgeoning Data Science problems.

This role is hands-on across all areas as a data scientist; from understanding customer requirements and collecting data, to developing visualizations and advanced analytics to make data-driven recommendations and decisions. You will work directly with intel analysts to develop prototypes and novel solutions that satisfy complex operational needs. 
  

Now on to the fun of formal requirements - we have to apologize in advance for the corporate-speak here, but just hold your breath for a few lines and everything will be okay. We are actively hiring data professionals for roles across a broad range of skill levels and projects. Our goal is to find the best fit for you so please note that if you apply to one of them and we see a fit elsewhere we will let you know. So do not worry about applying initially for every position you might be interested in.

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:     

• Large dataset experience
• Strong familiarity with data science applications such as association analysis, graph/network analytics, clustering, text analytics, classification and regression (multivariate and logistic).
• Training in the design and implementation of static and dynamic visualizations in R, Python, Tableau, or similar visualization software.

These are important skills to have, but not necessarily mandatory:     

• Exceptional interpersonal skills. You know, as in you might not be at the top of the list to be a game show host, but you do like people and enjoy solving problems jointly with your colleagues.
• Experience or exposure to Natural Language Processing (NLP).
• Experience with Java, C, or other compiled languages
• Comprehensive knowledge of Saturday Night Live sketches (just kidding)
• Experience with SQL/NoSQL, Spark, Hadoop
• Familiarity with Javascript and Scripting
• Familiarity with Docker, GitLab, and React

The total package: