Senior Data Scientist

Focused on the use of proprietary, AI-powered technology to increase efficiencies in the B2B ordering process, Conexiom's rapid growth stems from its ability to serve its customers with solutions that connect directly into their ERP systems and provide automation with 100 percent accuracy. We continue to build on our core technology to better serve manufacturers and distributors, allowing them to increase the speed and accuracy at which they serve customers, while also providing an opportunity to reallocate time from data entry to customer service. Conexiom delivers touchless automation associated with the manual processing of purchase orders and other business documents through its AI-enabled automation platform. As a Senior Data Scientist on the Product Engineering Team, you will be working in a fast-paced Agile environment with a proven product and team members who will work alongside you as you take the next steps in your career with us. KEY QUALIFICATIONS
• 5+ years' experience in implementing scalable ML systems into the production environment.
• Strong experience in all parts of the lifecycle of ML projects, including initial conceptualization, data handling, model development, and deployment.
• Strong proficiency in programming languages, including Python.
• Strong experience developing Python APIs using tools such as FastAPI.
• Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Scikit-Learn, etc.
• Experience with Generative AI models as well as techniques/patterns
• Knowledge of database technologies (SQL, MongoDB, Databricks) and data pipeline tools.
• Familiar with ML CI/CD pipelines for development, testing, versioning, and task automation.
• Familiar with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
• Experience building an enterprise-class business automation solution is a plus.
• Experience working in a SaaS environment a plus.
• Master's degree or PHD (preferred) in Computer Science, Data Science, Machine Learning, Statistics, or a related field KEY RESPONSIBILITIES
• Experiments with various machine learning algorithms and techniques to identify the most suitable ones for given tasks.
• Conducts and validates model performance through comprehensive evaluation metrics.
• Analyzes large datasets to extract actionable insights and trends.
• Implements machine learning models into production environments, ensuring scalability and reliability.
• Monitors and maintains the performance of deployed models, making updates and improvements as necessary.
• Works closely with and takes directions from our Engineering Managers.
• Collaborates effectively with other Software Engineers, Data Engineers and Data Scientists.
• Stays updated with the latest advancements in Machine Learning, AI, and Data Science