Join Hypergiant, an Accelint company, as a Data Scientist II and help organizations harness AI and machine learning to solve complex problems. You’ll design, build, and deploy predictive models using cloud platforms like GCP, BigQuery, and Vertex AI, contributing to data-driven decision-making across industries including defense, healthcare, energy, and aviation. Your work will directly impact business outcomes and enable clients to leverage AI for strategic insights.
Data Scientist II Responsibilities
- Develop, train, and deploy machine learning, deep learning, and optimization models for predictive and prescriptive analytics.
- Explore, clean, and transform large, complex datasets to extract actionable insights.
- Build and optimize SQL queries and data pipelines using BigQuery for feature engineering and performance.
- Implement models using Vertex AI, ensuring scalability, robustness, and maintainability.
- Apply statistical, mathematical, and optimization techniques to improve model accuracy and efficiency.
- Contribute to reusable components and shared libraries for standardizing experimentation and deployment.
- Collaborate with product, engineering, and analyst teams to align model outcomes with business objectives.
- Communicate findings through dashboards, visualizations, and presentations to technical and non-technical stakeholders.
- Maintain model reliability, explainability, and compliance with ethical AI standards.
- Stay current with trends in machine learning, generative AI, and MLOps to drive innovation.
Required Experience
- 2–5 years of professional data science experience.
- 2+ years working with GCP, BigQuery, and Vertex AI.
- Proficiency in Python (pandas, scikit-learn, TensorFlow, PyTorch).
- Knowledge of Spark framework and machine learning/deep learning algorithms.
- Experience building and deploying models into production environments.
- Strong SQL skills and experience with structured, semi-structured, and unstructured data.
- Familiarity with Git, CI/CD pipelines, and agile workflows.
- Degree in Computer Science, Statistics, Applied Mathematics, Data Science, or a related field.
Preferred Experience
- Exposure to AWS, Azure, or hybrid cloud architectures.
- Familiarity with MLOps, model monitoring, and automated retraining.
- Experience with NLP, computer vision, or time-series modeling.
- Knowledge of TFX, Kubeflow, MLflow, or Airflow for model orchestration.
- Understanding of generative AI, including prompt engineering and retrieval-augmented generation (RAG).
- Strong documentation, visualization, and storytelling skills to communicate insights effectively.
Benefits
- Unlimited Paid Time Off and 14 Company Holidays
- Paid Maternity/Paternity Leave
- Flexible Work Environment with Remote Options
- Medical, Dental & Vision Insurance, Optional HSA/FSA
- Complimentary Life Insurance
- Professional Development Reimbursement
- Short & Long Term Disability Insurance
- 401(k) with Matching
US Base Salary Range: $92,800–$130,000 USD
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