Job Number: R0134493
Machine Learning Engineer, Senior
Are you excited at the prospect of unlocking the secrets held by a data set? Are you fascinated by the possibilities presented by the IoT, machine learning, and artificial intelligence advances? In an increasingly connected world, massive amounts of structured and unstructured data open up new opportunities. As a Machine Learning Engineer, you can turn these complex data sets into useful information to solve global challenges. Across private and public sectors - from fraud detection, to cancer research, to national intelligence - you know the answers are in the data.
We have an opportunity for you to use your leadership and analytical skills to improve a client's machine learning capability. You'll work closely with your client to understand their questions and needs, and then dig into their data-rich environment to find the pieces of their information puzzle. You'll mentor teammates and use the right combination of tools and frameworks to turn that set of disparate data points into objective answers to help leadership make informed decisions. You'll provide your customer with a deep understanding of their data, what it all means, and how they can use it. Join us as we use data science for good in building this capability.
We are seeking candidates with a passion for machine learning and what it can bring to our clients. If you are an individual that gets excited by data, building predictive models, and briefing stakeholders on compelling results and next-generation technologies, we can provide an incredible opportunity to generate tangible impact in national defense.
Empower change with us.
-4+ years of experience in the data science field, including providing analysis and advice
-2+ years of experience with Python or R
-2+ years of experience with scikit-learn (Python), or Caret (R)
-Experience with building and optimizing data pipelines, architectures, and data sets for machine learning workflows
-Experience with visualizing data and producing high quality graphs and charts of machine learning results via matplotlib, seaborn, ggplot, or framework
-Experience with the preparation and development of senior leadership level background papers, reports, and speeches
Nice If You Have:
-Knowledge of supervised machine learning capabilities, including gradient boosting, random forests, linear/logistic regression, neural networks
-Knowledge of unsupervised machine learning methods, including LDA, KNN
-Knowledge of dimensionality reduction techniques, including PCA, NMF, and t-SNE, as well as their use cases and drawbacks
-Knowledge of model explainability and how modeling techniques can impact explainability
Applicants selected will be subject to a security investigation and may need to meet eligibility requirements for access to classified information; TS/SCI clearance is required.
Build Your Career:
When you join Booz Allen, you'll have the opportunity to connect with other professionals doing similar work across multiple markets. You'll share best practices and work through challenges as you gain experience and mentoring to develop your career. In addition, you'll have access to a wealth of training resources through our Analytics University, an online learning portal where you can access more than 5000 functional and technical courses, certifications, and books. Build your technical skills through hands-on training on the latest tools and state-of-the-art tech from our in-house experts. Pursuing certifications that directly impact your role? You may be able to take advantage of our tuition assistance, on-site bootcamps, certification training, academic programs, vendor relationships, and a network of professionals who can give you helpful tips. We'll help you develop the career you want as you chart your own course for success.
We're an equal employment opportunity/affirmative action employer that empowers our people to fearlessly drive change - no matter their race, color, ethnicity, religion, sex (including pregnancy, childbirth, lactation, or related medical conditions), national origin, ancestry, age, marital status, sexual orientation, gender identity and expression, disability, veteran status, military or uniformed service member status, genetic information, or any other status protected by applicable federal, state, local, or international law.