Data Scientist

M9 Solutions is seeking a Data Scientist to work hybrid remote/on-site on a government contract for a client located in Washington, DC. An active TS/SCI clearance is required.

Responsibilities

• Be involved in full spectrum analytic technical support tasks, such as requirements collection and refinement, translating user requirements into technical requirements, environment configuration, exploratory data analysis, model development, selection, evaluation, identifying insights from analytic products and then communicating those results to a nontechnical audience.
• Work with cross-functional teams to identify relevant and permissible data sources, access available infrastructure, and develop analytic products tailored to mission user requirements.
• Produce analytic products that clearly and succinctly distill trends, illuminate latent patterns, and spotlight insights in an easy-to-consume manner for customers to take action on.
• Define and communicate a clear product vision for the customer’s software products, aligning with user needs and business objectives.
• Create and manage product roadmaps that reflect both innovation and growth strategies.
• Document customer requirements to be used for project management.
• Develop technical architecture that supports development approach.
• Forecast and outline technical tasks that guide weekly development in support of technical projects.
• Partner with a government product owner and collaborate with a Data Science team of 5 – 8 individuals.

Required Skills & Qualifications

• Ability to work on-site in Washington, DC on a hybrid schedule.
• Active TS/SCI security clearance.
• STEM Bachelor’s degree and 6 – 8+ years of relevant experience, or STEM Master’s degree and 4 – 6+ years of relevant experience, or 10 – 12+ years of relevant experience in lieu of a degree.
• Hands-on experience implementing, training, and evaluating deep learning models with familiarity of adversarial, semi-supervised, and generative architectures.
• Hands-on experience working with Torch, TensorFlow, and similar machine learning frameworks.
• Skilled in evaluating machine learning models using various metrics beyond accuracy and implementing strategies to improve performance.
• Hands-on experience using statistical and machine learning techniques to model, characterize, and extract meaning from structured and unstructured data.
• Experience executing data science methods using Python libraries for Data Cleaning/Wrangling, Exploratory Data Analysis (EDA), Statistical Analysis, Data Visualization.
• Hands-on experience in object-oriented programming with a language such as C++, Java, or Python (Python as primary programming languages).
• Hands-on experience working on source controlled code with a functional team in a tool like Git or Subversion.
• Hands-on experience programmatically interacting with cloud (e.g.: Amazon Web Service (AWS)) services and products.
• Experience using or exposure to Python libraries such as pandas, NumPy, GeoPandas, requests, urlib3, Matplotlib, plotly, scikit-learn, sciPy, OpenCV, GDAL, Keras, NLTK, spaCy, Gensim.
• Strong strategic communication skills to include presenting quantitative concepts in easy-to-understand formats and actively listening to identify business problems and their causes.
• Strong interpersonal skills.
• Skills & Technologies:
  • Technical Documentation
  • Statistics, Mathematics
  • Natural Language Processing (NLP)
  • Atlassian Confluence
  • JIRA
  • Github
  • GitLab
  • Gitlab Administration
  • Data Analytics Tool
  • Amazon Web Services (AWS)
  • Amazon Sagemaker
  • Amazon AWS

Preferred Skills & Qualifications

• Hands-on experience implementing generative AI (Gen AI) models.
• Hands-on experience implementing Retrieval Augmented Generation (RAG) in Gen AI solutions.
• Experience implementing advanced NLP machine learning models on tasks such as entity resolution, question and answering, and text summarization.
• Experience developing and deploying data science solutions in containers.
• Experience/familiarity with interacting programmatically with data stores and analytic services.
• Working knowledge and experience in accessing remote APIs using cryptographic keys and digital certificates.
• Experience extracting features from data stored in a wide range of possible formats including JSON, XML, raw text logs, industry-specific encodings, and graph link data.
• Working knowledge of collaboration tools such as Jira and Confluence.