
Data Scientist - Multiple Levels (TS/SCI with Poly Required)
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Job Description
Description
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:
- Data Architecture: Become an expert in characterizing, identifying and cataloging disparate datasets across multiple networks, systems and repositories while leveraging analytic/statistics for discovery and insight.
- Data Engineering: Apply streaming and storage strategies for data-in-transit and data-at-rest respectively. Design and implement high-performance and efficient data catalogs and structures for maximal throughput and minimal overhead for queries and other types of interactions with large datasets.
- Data Science: Apply natural language processing and machine learning/AI advanced techniques to train and optimize models for automating analysis, processes and insight. Deploy these trained models and processes to work on production at scale while leveraging the amenities of a commercial cloud environment - e.g. automatic scaling of the deployment and runtime of prototypes and workflows to distributed clusters.
- Data Visualization: Create visualizations using custom-developed dashboards and/or industry standard commercial platforms to present actionable insights and interactive interfaces.
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:
- 16+ years experience in a similar work environment using the described technologies below. Any combination of the following acceptable criteria will be considered for work experience equivalence: Professional work experience history; Relevant technical certifications; Undergraduate degree in Computer Science, Information Systems, Engineering, Business, or a related field in a technical/scientific discipline; Graduate degree in a related field or discipline; Doctorate in a related field or discipline.
- Python development with expertise in Python data packages: pandas, numpy, scipy, gensim, scikit-learn
- Experience with ML technologies - TensorFlow, PyTorch, Jupyter notebooks, etc.
- Programming experience with implementation of machine learning models on textual data and structured datasets
- Experience with working on data visualization technologies - Kibana, Bokeh, Leaflet/Folium, Tableau, Splunk, etc.
- Development experience in commercial cloud environments - Amazon Web Service, Azure, etc.
- Experience with ElasticSearch indexes, SQL data repositories - structured and unstructured
- Experience with data workflow frameworks - Apache NiFi
- Familiarity with industry best practices for Agile software development, automated testing, and continuous integration
These are important skills to have, but not necessarily mandatory:
- AWS Cloud development and infrastructure management
- Master’s degree or higher education in Computer Science, Mathematics, Data Science, Statistics or a related field or discipline
- Demonstrated professional experience with computer networks, digital forensics and cybersecurity
The total package:
- Disclosed pay ranges are a general guideline, and are not a guarantee of a final salary or compensation. Our approach in determining final salaries takes into consideration a number of factors such as education, certifications, total years of relevant professional experience, actual level of expertise, and the responsibilities of the role itself.
- Based on the outlined roles, responsibilities, and requirements, the projected pay range for this position is $190,000 - $250,000.
- Retire sooner than planned: Get closer to retirement with up to 10% in 401k contributions, immediately vested.
- Have a career AND a life: Enjoy up to 5 weeks of leave (25 days of personal time off) and 11 paid floating holidays.
- Stay at your best: As a member, we'll pay 100% of your premiums for comprehensive health, dental, and vision insurance. We'll also pay the majority of the premiums for your family. Let's not forge free access to a fully equipped state of the art gym!
- Keep current on new technologies and technological advancements: $5250 per year towards ongoing education, trainings, certifications, and maintaining professional memberships.
- Dress in style: Spend up to $300 per year on company branded merchandise featuring top quality brands such as Under Armour, Nike, Carhartt, YETI, etc.
- Enjoy the culture: Attend fun company events throughout the year such as our Oktoberfest, summer picnic, and annual holiday party! These are all in additon to your team events which may include happy hours, baseball games, snowboarding, RenFest, and more!