Machine Learning Data Scientist

Nashville, Tennessee, United States | Core Engine | Full-time | Fully remote

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ABOUT ITEMIZE 

Itemize is a leading AI company that transforms financial documents into valuable and efficient information sets for business systems. We harness AI to transform unstructured and semi-structured data in purchase documents, such as invoices and receipts, into structured data for accounts payable and accounting systems.

Our intelligent document processing technology empowers financial teams to focus on higher-value activities by liberating them from laborious and costly data entry and reconciliation tasks, which remain manual processes.

Itemize operations are cloud-based, with a fully remote team distributed nationwide. The company runs on an East Coast schedule. We welcome people who enjoy the challenge of a fast-paced high-growth environment on the leading edge of B2B SaaS technology. 

 

ABOUT THE ROLE

The Machine Learning Data Scientist will join a team of engineers innovating new techniques for applying Artificial Intelligence, Machine Learning, and data analytics techniques to transform unstructured images and files into financial data sets

The Machine Learning Data Scientist’s responsibilities will include:

  • Develop machine-learning models, services, and modules for document classification and information extraction 
  • Build pipelines and processes for model development, experimentation and scaled production scoring
  • Identify and develop new modeling techniques and/or technologies to complement existing ML processes and improve extraction rates and confidence
  • Measure, improve, and validate confidence scores through rigorous and continuous testing
  • Improve verification and validation functionality
  • Apply machine learning and data science techniques and design distributed systems

 

SKILLS AND EXPERIENCE

  •  Bachelor’s Degree in Computer Science or Engineering
  • 3+ years software development experience in a professional work environment
  • Strong software engineering background with emphasis in data science and machine learning
  • Experience in some of the following ML frameworks: Tensorflow, pandas, pytorch, xgboost, numpy, keras, scikit-learn, dask, spark
  • Demonstrable knowledge and understanding of Statistics and Deep Learning concepts
  • Understanding of probability and statistics and machine learning concepts such as precision, recall, optimization, hyperparameter tuning, overfitting, and interpretability
  • Understanding of how components and processes work together and communicate with each other using library calls, RESTful APIs queueing/messaging systems and database queries
  • Familiar with SQL, and able to create/perform basic queries
  • Fluent in Linux based systems, Docker, and code versioning tooling (Git/CI/CD)
  • Familiarity with AWS cloud services
  • Strong interpersonal communications skills (verbal, presentation, and written)

 

WHAT WE OFFER

  • High energy atmosphere of an AI-driven FinTech scaleup that has great traction towards global success and already serves clients across four continents, including Fortune 500 companies. And we are just getting started!
  • We value education and professional development and encourage employees to take ownership, become subject matter experts, and bring new ideas to the table to challenge themselves and their teammates.
  • Enjoyable working environment: A diverse international team of techies, dog lovers, globetrotters, and musicians. We offer flexible PTO and a generous benefits package, and highly value independence. Our team enjoys spending time together with fun virtual activities and we look forward to re-establishing face to face events soon!


Candidates must be authorized to work in the United States and available to work East Coast business hours.

Itemize is an Equal Opportunity Employer. Itemize does not discriminate on the basis of race, religion, color, sex, gender identity, sexual orientation, age, non-disqualifying physical or mental disability, national origin, veteran status or any other basis covered by applicable law. All employment is decided on the basis of qualifications, merit, and business need.