ICA, Inc.

Data Scientist

• Identify Opportunities: Collaborate with internal and external stakeholders to uncover and define data-driven opportunities that align with strategic business goals.
• Data Analysis & Modeling: Mine and analyze complex datasets from company and client databases to drive product and business optimization strategies, using both traditional statistical techniques and state-of-the-art machine learning approaches.
• Assess the effectiveness and accuracy of new data sources and data gathering techniques, including evaluating and implementing methods for acquiring and processing large volumes of text data.
• Perform data processing using State of the Art LLM Models and technologies
• Innovation & Strategy: Assess the effectiveness of new data sources and data gathering techniques, identifying ways to enhance the organization’s data strategy with novel ML and AI methods.
• Client-Facing Presentations: Develop compelling presentations and demos to showcase analytical solutions and insights to both technical and non-technical audiences, including clients and senior management.
• Predictive Modeling & Optimization: Use advanced statistical and machine learning approaches to drive improvements in customer engagement, product performance, and business processes.
• Model Monitoring: Establish processes and tools to track model performance, data accuracy, and reliability over time. Continuously iterate on models to meet evolving business needs and industry best practices.

Data Science, Machine Learning Engineer

Machine Learning Engineer

• Study and transform data science prototypes
• Solve complex problems with multilayered data sets, and optimize existing machine learning libraries and frameworks
• Design machine learning systems
• Research and implement appropriate ML algorithms and tools
• Develop machine learning applications according to requirements
• Run machine learning tests and experiments
• Perform statistical analysis and fine-tuning using test results
• Extend existing ML libraries and frameworks
• Optimize machine learning algorithms for performance, scalability, and reliability
• Stay updated with the latest machine learning techniques and technologies, and proactively identify opportunities to apply them in our context
• Collaborate with data engineers and scientists to build efficient data pipelines for training and deploying machine learning models
• Monitor and maintain the performance of deployed models, and iterate on them to continuously improve results

Data Engineer

• Design and maintain scalable data pipelines and ETL/ELT processes
• Build document processing pipelines for text and image extraction
• Architect AWS-based data solutions using S3, Glue, Redshift, RDS, ECS, etc
• Optimize SQL queries and develop Python-based data processing workflows
• Troubleshoot data pipeline issues and implement solutions
• Ensure data pipeline performance, scalability, and security

Scrum Master / Agile Coach

• Lead Scrum ceremonies and Agile facilitation: daily stand-ups, sprint planning, retrospectives, sprint reviews
• Guide teams on Agile/Scrum best practices and remove impediments
• Track and report key Agile metrics and coach team members
• Perform technical analysis of user stories and requirements and translate into actionable development tasks
• Conduct code reviews and provide technical guidance to ensure quality standards
• Contribute to technical documentation and maintain code integrity
• Participate in solution design discussions and architectural decisions
• Troubleshoot technical blockers and provide hands-on support when needed
• Collaborate with Team Leads, data scientists, engineers, and analysts to prioritize technical backlogs and ensure feasibility
• Support multiple Scrum teams and coordinate dependencies between technical initiatives
• Help develop prototype/MVP for FDA applications and scale to productionized tool

Scrum Master/Project Coordinator

DevOps Engineer

• Manage and optimize our AWS infrastructure while ensuring robust security and compliance standards
• Maintain CI/CD pipelines, implement monitoring and observability systems, and support regulatory compliance requirements
• Contribute to developing a working prototype or MVP designed to pilot various prioritized applications for the FDA
• Utilize an Agile development framework to help develop an initial prototype before scaling it into a fully productionized tool
• Own and evolve AWS infra (ECS/Fargate, RDS/Postgres, S3, IAM, VPC)
• Maintain and improve CI/CD pipelines (GitHub Actions) and Infra-as-Code (Terraform)
• Set up alerting, log aggregation, and performance dashboards (CloudWatch, Datadog, or OpenTelemetry)
• Implement secure-by-default practices; support SOC 2 / HIPAA readiness
• Write Python/Bash scripts for backups, monitoring, deployment hooks, etc.
• Assist with Postgres tuning, access control, and migrations
• Lay groundwork for container orchestration (EKS/Kubernetes) if/when we scale beyond ECS

Data Science, Machine Learning Engineer

Machine Learning Engineer

Data Engineer

Scrum Master/Project Coordinator

DevOps/DevSecOps Engineer