Data Scientist

Company Background

Join us at Mi-Case, where we’re at the forefront of developing innovative public safety products and solutions. We take pride in delivering fully-integrated software and exceptional client support, making a real impact in communities. As part of our team, you’ll collaborate with passionate, talented colleagues and industry experts who are deeply committed to solving the unique challenges faced by our clients in the public safety sector. Together, we’re replacing outdated systems with cutting-edge, mobile-ready solutions that empower our clients to enhance public safety and achieve their goals.

Position Summary

We are seeking a skilled Data Scientist to develop and implement machine learning models and AI-driven solutions for our public safety platforms. In this role, you will leverage advanced tools like AWS tools such as Bedrock, SageMaker, QuickSight, and similar tools to build scalable AI/ML models and deliver insights through data visualization. These solutions will improve operational efficiency, data-driven decision-making, and predictive analytics for public safety applications. Strong communication skills are essential for collaborating with cross-functional teams and translating data insights into actionable strategies for stakeholders.

As a data science expert, you will work closely with developers, data engineers, and system SMEs to ensure that AI models, data solutions, and visualizations are optimized and seamlessly integrated into our platforms. You will focus on building, deploying, and fine-tuning machine learning models, as well as visualizing data insights to enable informed decision-making for our clients.

Role:

• Design, develop, and implement machine learning models using tools like AWS Bedrock, SageMaker, QuickSight, and other AWS services to address public safety challenges.
• Collaborate with developers, data engineers, and system SMEs to identify opportunities for AI-driven improvements and solutions, while providing insightful visualizations of key metrics using AWS QuickSight.
• Build and train predictive models to enhance decision-making processes and operational efficiency.
• Conduct data analysis, feature engineering, and visualization to ensure data quality and improve model performance.
• Use AWS QuickSight to build interactive dashboards and reports, presenting complex data findings in a clear, actionable way for clients and stakeholders, and business leaders.
• Monitor model performance, ensuring ongoing accuracy and reliability, and troubleshoot any issues that arise in production environments.
• Document processes, data science methodologies, and model outputs for transparency and future reference.

Minimum Years of Experience: 7 Years

Education and skills:

• Experience: 4+ years of experience in data science, machine learning, or a related field.
• Education: Bachelor’s degree in Computer Science, Data Science, Machine Learning, or a related field. Master’s degree preferred.
• Proficiency with machine learning frameworks (e.g., TensorFlow, PyTorch) and cloud platforms (e.g., Amazon SageMaker, Bedrock, QuickSight).
• Strong programming skills in Python, with experience in data manipulation, analysis, and visualization.
• Experience building, training, and deploying ML models using AWS services, along with creating data visualizations in AWS QuickSight.
• Excellent communication skills with the ability to present complex technical concepts and visualizations to non-technical stakeholders.
• Strong analytical and problem-solving skills with a focus on innovation.
• Experience with data preprocessing, feature engineering, and model optimization.

Nice to Have:

• Experience with data governance and compliance best practices in AI/ML projects.
• Familiarity with large-scale data processing tools like Apache Spark.
• Experience with deep learning frameworks and NLP models.

Job Types: Full-time, Exempt

Salary: $110,000-$130,000 per year

Benefits:

• 401(k) 3% Match
• 401(k) matching
• Dental insurance
• Flexible spending account
• Health insurance
• Health savings account
• Life insurance
• Paid holidays
• Paid time off
• Professional development assistance
• Vision insurance
• Work from home

Location: United States-Remote