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🤖 Closed by robot after apply link errored w/ code 404 3 years ago
\nABOUT THE ROLE\n\nThe 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.\n\nThe Machine Learning Data Scientist’s responsibilities will include:\n\n\n* Develop machine-learning models, services, and modules for document classification and information extraction\n\n* Build pipelines and processes for model development, experimentation and scaled production scoring\n\n* Identify and develop new modeling techniques and/or technologies to complement existing ML processes and improve extraction rates and confidence\n\n* Measure, improve, and validate confidence scores through rigorous and continuous testing\n\n* Improve verification and validation functionality\n\n* Apply machine learning and data science techniques and design distributed systems\n\n\n\n\nSKILLS AND EXPERIENCE\n\n\n* Bachelor’s Degree in Computer Science or Engineering\n\n* 3+ years software development experience in a professional work environment\n\n* Strong software engineering background with emphasis in data science and machine learning\n\n* Experience in some of the following ML frameworks: Tensorflow, pandas, pytorch, xgboost, numpy, keras, scikit-learn, dask, spark\n\n* Demonstrable knowledge and understanding of Statistics and Deep Learning concepts\n\n* Understanding of probability and statistics and machine learning concepts such as precision, recall, optimization, hyperparameter tuning, overfitting, and interpretability\n\n* Understanding of how components and processes work together and communicate with each other using library calls, RESTful APIs queueing/messaging systems and database queries\n\n* Familiar with SQL, and able to create/perform basic queries\n\n* Fluent in Linux based systems, Docker, and code versioning tooling (Git/CI/CD)\n\n* Familiarity with AWS cloud services\n\n* Strong interpersonal communications skills (verbal, presentation, and written)\n\n\n\n\nWHAT WE OFFER\n\n\n* 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!\n\n* We value education and professional development and offer opportunities for our employees to grow and learn in their roles and within the industry\n\n* 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!\n\n\n\n\n\nItemize 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. \n\n#Salary and compensation\n
No salary data published by company so we estimated salary based on similar jobs related to Machine Learning, Education, Finance, Cloud, Linux and Non Tech jobs that are similar:\n\n
$70,000 — $120,000/year\n
\n\n#Benefits\n
💰 401(k)\n\n🌎 Distributed team\n\n⏰ Async\n\n🤓 Vision insurance\n\n🦷 Dental insurance\n\n🚑 Medical insurance\n\n🏖 Unlimited vacation\n\n🏖 Paid time off\n\n📆 4 day workweek\n\n💰 401k matching\n\n🏔 Company retreats\n\n🏬 Coworking budget\n\n📚 Learning budget\n\n💪 Free gym membership\n\n🧘 Mental wellness budget\n\n🖥 Home office budget\n\n🥧 Pay in crypto\n\n🥸 Pseudonymous\n\n💰 Profit sharing\n\n💰 Equity compensation\n\n⬜️ No whiteboard interview\n\n👀 No monitoring system\n\n🚫 No politics at work\n\n🎅 We hire old (and young)\n\n
# How do you apply?\n\nThis job post has been closed by the poster, which means they probably have enough applicants now. Please do not apply.
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