Kensho ML engineers tackle a wide range of machine learning problems from timeseries prediction to natural language processing, but all are passionate about building machine learning systems on real world data. You should have extensive experience applying a range of machine learning models to a diverse set of problems. You should enjoy moving beyond the theoretic confines of academia to applying your tradecraft in the real world and producing data driven products that will empower decision makers at all levels of the global banking industry and beyond. The ideal candidate is precise and detail oriented. Most importantly, a Kensho machine learning engineer is excited at the opportunity to work in a lean, tight-knit startup bringing transparency to some of the most important issues on the planet.

What You’ll Do:

• Conduct original research on large proprietary and open source data sets
• Identify, research, prototype and build predictive products
• Build cutting edge models for understanding vast amounts of textual data
• Write production-ready code 
• Write tests to ensure the robustness and reliability of your productionized models

What We Look For:

• At least one core programming expertise, such as python (NumPy, SciPy, Pandas), MATLAB, or R
• Experience with advanced machine learning methods
• Strong statistical knowledge, intuition and experience applying machine learning models to real data
• Stellar ability to communicate even the most complicated methods and results to a broad, often non-technical audience 
• Effective coding, documentation and communication habits
• Ability and credibility to lead a team
• Experience at a top technology company or financial institution
• Several of the following terms should hold deep meaning for you: lookahead bias, bagging, boosting, stacking, information retrieval, entity recognition, bootstrapping, LSTM, Glorot initialization, Kullback-Leibler divergence, GLOVE, SMAPE, HMM, MAP, exponential family, VC dimension, EM, L1, TD(Lambda) 

How to Really Get Our Attention:

• Major machine learning contributor at a top company or university
• Significant experience at a top financial analytics company or hedge fund
• Your github/kaggle account showing entrepreneurial yet practical initiative

Technologies We Like:

• Python and specifically Numpy, SciPy, Pandas, scikit-learn
• Neural network packages like TensorFlow and Torch
• ML packages like LightGBM and XGBoost

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin. kensho.com