Lead Data Scientist
United States
Conexiom
Instantly turn unstructured trade documents into structured data with The Conexiom Platform.
Lead Data ScientistOur fully automated, purpose-built solution eliminates the manual processing of business-critical commercial documents with 100% data accurate, touchless transactions. Thesedocuments include purchase orders, invoices, advance shipping notices, and other essentialcommercial documents exchanged between business and their customers. About the Opportunity:With Conexiom's ongoing significant growth, we are propelling our data science endeavorsfurther. As a Lead Data Scientist at Conexiom, you’ll serve as the technical lead, providingstrategic guidance in selecting modeling approaches and mentoring a talented team, whileremaining deeply hands-on. Responsibilities:
- Serve as the technical lead in defining and refining our modeling approach, balancing traditional machine learning methods with Large Language Models (LLMs) to achieve optimal results.
- Drive architectural decisions for deep learning models, working closely with engineers to ensure scalability, efficiency, and maintainability.
- Lead by example, working hands-on with datasets, EDA, models, and implements in production, spending approximately 90% of your time on direct technical work.
- Offer thought leadership by deeply analyzing complex problems, identifying underlying patterns, and critically evaluating solutions for data science challenges.
- Mentor Senior Data Scientists and other team members, fostering technical growth and promoting best practices in model development and deployment.
- Collaborate with the Chief Data Scientist to align data science strategy with business objectives and provide input on high-level goals and projects.
- Master’s or Ph.D. degree in Computer Science, Data Science, Machine Learning, Statistics, or a related field.
- 5+ years’ experience in developing and deploying machine learning models, including at least 2 years in technical leadership capacity.
- Expertise in both traditional ML techniques and experience with Large Language Models, including hands-on experience with fine-tuning and application of LLMs.
- Advanced knowledge of deep learning architectures and the ability to make architectural decisions that impact performance and scalability.
- Strong proficiency in Python, along with experience in machine learning libraries and frameworks such as TensorFlow, PyTorch, and Scikit-Learn.• Ability to translate business problems into structured data science tasks and effectively communicate findings and recommendations.
- Experience in a SaaS environment and knowledge of enterprise-class business automation solutions is a plus.
- Passion for continuous learning and staying current with advancements in machine learning and AI.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
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Categories:
Data Science Jobs
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Tags: Architecture Computer Science Deep Learning EDA LLMs Machine Learning ML models Python PyTorch Scikit-learn Statistics TensorFlow
Perks/benefits: Career development Competitive pay Health care
Region:
North America
Country:
United States
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