QxBranch is seeking a talented data scientist with a background in machine learning and taking data science solutions through to production. The successful applicant will be invited to join our welcoming, diverse team in Washington DC and work on innovative solutions to diverse problems. The role will require you to interact with clients and collaborate with QxBranch's passionate team of data scientists and systems engineers, shaping data analytics solutions to meet client needs. Responsibilities: • Prototype, develop, and deploy complex analytics models for client systems • Organize, manage, and curate large and complex datasets • Work in an internationally distributed team, with schedule flexibility • Deliver high quality technical outcomes while adhering to cost and schedule constraints • Continue technical and professional development to ensure QxBranch technology remains on the cutting edge Qualifications Education and Experience: • Proficiency in Python and common machine learning packages such as scikit-learn, NLTK, and Theano • Competence in all portions of the data analytics pipeline, including ingest, cleaning, feature extraction, modeling, statistical validation, and visualization / reporting • Competence in software development practices including writing maintainable code, unit testing, version control, cloud-based development and performance profiling and tuning • Bachelor of Science or higher in engineering, science, or mathematics, with specializations related to computer science preferred • Minimum of 4 to 6 years relevant experience, including internships, part-time positions, and graduate level education Desired Skills: • Expertise in one or more of: natural language processing, probabilistic modeling, time series analysis, anomaly detection, deep learning, behavioral analysis, causal analysis • Strong data visualization and data "storytelling" skills • Analytics experience in finance, insurance, and/or cyber security • Proficiency in other analytics technologies, such as R, SQL, CUDA, Hadoop, and Spark • Experience with Dataiku's Data Science Studio