Data Scientist II

Hypergiant, an Accelint company, empowers forward-thinking organizations with AI-driven solutions to stay ahead. Our geographic presence spans the U.S. and allied partners, with facilities in key Defense Technology hubs from Southern California to Washington, D.C. We provide large enterprises – across industries like the Defense Department, energy, healthcare, and aviation – with bespoke technology solutions, cutting-edge advice, and deployment expertise needed to harness the value out of artificial intelligence and machine learning. At our core, we are military experts, researchers, and technologists who want to accelerate intelligence to deliver strategic insights that turn future challenges into today’s opportunities.

We are seeking a Data Scientist II to join our agile, multidisciplinary team and contribute to the development of advanced analytical models that power data-driven decision-making. The ideal candidate will be a hands-on problem solver who can build, test, and deploy predictive models, integrate them into production systems, and collaborate closely with cross-functional teams to deliver measurable business value.

You will work alongside other data scientists, engineers, and product teams to design and implement scalable data science solutions using cloud technologies—particularly on Google Cloud Platform (GCP) with BigQuery and Vertex AI.

Role & Responsibilities:

• Design, build, and continuously improve machine learning, deep learning, and optimization models to support predictive and prescriptive analytics.
• Explore, clean, and transform large and complex datasets to extract actionable insights and support modeling pipelines.
• Create and optimize SQL queries and data pipelines leveraging BigQuery for data preparation, feature engineering, and performance optimization.
• Develop, train, and evaluate models using Vertex AI, ensuring scalability, robustness, and maintainability in cloud-based deployments.
• Apply statistical, mathematical, and optimization techniques to solve complex business problems and improve model accuracy and efficiency.
• Contribute to reusable modeling components, shared libraries, and collaborative codebases for standardizing experimentation and deployment practices.
• Participate in the full model development lifecycle—including requirement gathering, model design, training, validation, deployment, and monitoring—within an agile, iterative framework.
• Collaborate with product owners, analysts, and engineers to define measurable objectives and align model outcomes with business needs.
• Communicate analytical findings and model results clearly through visualizations, dashboards, and presentations for both technical and non-technical stakeholders.
• Ensure model reliability, explainability, and ethical AI compliance through effective validation, peer review, and documentation.
• Stay current with emerging trends in machine learning, deep learning, generative AI, and MLOps to drive continuous innovation and technical excellence.

Required Experience:

• 2-5 years of professional data science experience.
• 2+ years of experience with GCP, specifically BigQuery and Vertex AI (required).
• Strong proficiency in Python (pandas, scikit-learn, TensorFlow, PyTorch, or similar)
• Knowledge of Spark Framework
• Solid understanding of machine learning, deep learning, and optimization algorithms
• Experience building, training, and deploying models using modern ML frameworks and integrating them into production environments.
• Proficiency in SQL and experience working with structured, semi-structured, and unstructured data.
• Familiarity with version control (Git), CI/CD pipelines, and collaborative agile workflows.
• Strong analytical thinking, problem-solving, and communication skills.
• Degree in Computer Science, Statistics, Applied Mathematics, Data Science, or a related field.

Preferred Experience:

• Experience with additional cloud platforms (AWS, Azure) or hybrid data architectures.
• Familiarity with MLOps, model monitoring, and automated retraining workflows.
• Exposure to natural language processing, computer vision, or time-series modeling.
• Experience with tools such as TensorFlow Extended (TFX), Kubeflow, MLflow, or Airflow for model orchestration.
• Understanding of generative AI principles, including prompt engineering, fine-tuning, and retrieval-augmented generation (RAG).
• Strong documentation, visualization, and storytelling skills to communicate insights effectively.

EEOC & Know Your Rights: Accelint companies are Equal Opportunity Employers. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, age, disability, status as a protected veteran or any other status protected by applicable federal, state, and local law. We ensure that all employment decisions, including hiring, promotion, compensation, and other terms and conditions of employment, are based on merit, qualifications, and business needs. For more information about your rights, please review the "Know Your Rights" poster from the Equal Employment Opportunity Commission (EEOC).

ADA: In compliance with the Americans with Disabilities Act (ADA), if you have a disability and would like to request an accommodation within the application and selection process, please contact careers@accelint.com.

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