Itemize

New York
11-50 employees
Transforming financial transaction processing for Accounts Payable, Receivables, Supply Chain, and Loan Processing through our advanced, Ai-powered platform.

Data Scientist

Data Scientist

ABOUT ITEMIZE

Itemize builds AI-powered Copilots that help automate Finance functions. The company provides specialized AI-ML solutions for corporate CFOs and financial services organizations. By harnessing cutting-edge technologies, Itemize streamlines and automates processes in areas including Accounts Payable (AP) and Accounts Receivable (AR). Itemize facilitates greater efficiency, better decision-making and improved risk mitigation.

Itemize operations are cloud-based, with teams distributed nationwide and internationally. We have teams coast to coast within the United States as well as in several countries worldwide. We welcome people who enjoy the challenge of a fast-paced, high-growth environment on the leading edge of applying AI to B2B financial challenges.

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 automate financial functions.

The Machine Learning Data Scientist’s responsibilities will include:

  • Identify and develop new modeling techniques and/or technologies to complement existing ML processes
  • Develop Python components, services, and modules for document classification, information extraction & interpretation
  • Measure, improve, and validate confidence scores through rigorous and continuous testing
  • Design and implement automated testing and feedback to improve model development and information extraction with high confidence
  • Identify relevant data sources to mine for business needs, and collect large structured and unstructured datasets and variables
  • Maintain documentation on components, processes, and test plans
  • Keep current with technical and industry developments
  • Communicate findings to all stakeholders

REQUIRED SKILLS AND EXPERIENCE

  • Bachelor’s Degree in Computer Science, Statistics, Mathematics, or related discipline
  • 5+ years experience in a professional work environment as a data-scientist
  • Experience in one or more ML toolkits or Python frameworks
  • Experience and demonstrable knowledge of Deep Learning concepts
  • Understanding of probability and statistics and machine learning concepts such as precision, recall, optimization, hyperparameter tuning, overfitting, and interpretability
  • Experience in applying standard implementations of machine learning algorithms effectively by choosing a suitable model such as decision tree, knn, neural net, or an ensemble of multiple models
  • Understanding of how components and processes work together and communicate with each other using library calls, REST APIs queueing/messaging systems and database queries
  • Understanding of system design to avoid bottlenecks and let your algorithms scale well with increasing volumes of data
  • Self-driven and self-guided in a dynamic environment

PREFERRED EXPERIENCE

  • Graduate (Master’s or Ph.D) Degree (or in progress) Preferred
  • Experience with PyTorch, NLTK, SciPy, Scikit-Learn, Numpy, OpenCV or equivalent for image preprocessing
  • Experience with SQL/NoSql databases and queries
  • Familiarity with coding best practices, OOD/OOP, modular design, SOA, and systems architecture

WHAT WE OFFER

  • High energy atmosphere of a growth-stage FinTech with great traction serving Fortune 500 companies operating in more than 25 countries
  • Professional development opportunities for learning and growth
  • A diverse international team of techies, dog lovers, globetrotters, and musicians
  • Itemize offers flexible PTO and a generous benefits package, and highly values independence
  • Salary range of $130-140k, depending on location and experience, as well as employee stock options

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.

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