The SPDJI Kensho team is part of S&P DJI and is an industry leader in the application of artificial intelligence to provide a systematic approach for investors to gain unique and differentiated insights and exposures. Our flagship family of indices describing the industries and innovation of the Fourth Industrial Revolution, the S&P Kensho New Economies, utilizes advanced natural language processing and topic modeling and is licensed to some of the largest asset managers in the world.
The team works in close partnership with the broader machine learning teams in Kensho and other parts of the organization while pursuing solutions that will shape the indices business in the years ahead.
What’s in it for you: You will be responsible for leading a small team of engineers to produce solutions in support of indices business, leveraging developments and data from across the organization, and contributing to the advancement of machine learning at S&P Global.
Responsibilities: As a senior Machine Learning Engineer, you will be responsible for tackling a wide range of problems from natural language processing to timeseries prediction. You will move beyond the theoretical confines of academia and apply your tradecraft to build machine learning systems on real world data. In this role you will constantly collaborate and work with groups of engineers. Our machine learning team is responsible for delivering ML-based solutions from problem framing, to prototyping, to production application.
· You will also conduct original research on large proprietary and open source data sets
· Identify, research, prototype, and build predictive products
· You will build cutting-edge models for understanding vast amounts of textual data
· Write production code
· You will write tests to ensure the robustness and reliability of your productionized models
· You will work closely with software engineers to build incredible systems
· You will guide and mentor team members and help educate the business on the art of the possible
· You have 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 modeling real data
· Ability to communicate even the most complicated methods and results to a broad, often non-technical audience
· Demonstrated effective coding, documentation, and communication habits
· Experience leading teams
· Several of the following terms should hold deep meaning for you: LSTM, lookahead bias, bagging, boosting, stacking, information retrieval, batch norm, entity recognition, bootstrapping, Glorot initialization, Kullback-Leibler divergence, GLOVE, SMAPE, HMM, MAP, exponential family, VC dimension, EM, L1, TD(Lambda)
· You have 3+ years of experience being a major machine learning contributor at a top company, hedge fund, or university
· You have the ability and credibility to lead a team
Technologies You Will Use
· Python and specifically Numpy, SciPy, Pandas, scikit-learn
· Neural network packages like TensorFlow and Keras
· ML packages like LightGBM and XGBoost
S&P Dow Jones Indices
At S&P Dow Jones Indices, our role can be described in one word: essential. We’re the largest global resource for index-based concepts, data and research, and home to iconic financial market indicators, such as the S&P 500® and the Dow Jones Industrial Average®. More assets are invested in products based upon our indices than any other index provider in the world; with over 1,000,000 indices, S&P Dow Jones Indices defines the way people measure and trade the markets. We provide essential intelligence that helps investors identify and capitalize on global opportunities.
S&P Dow Jones Indices is a division of S&P Global (NYSE: SPGI), which provides essential intelligence for individuals, companies and governments to make decisions with confidence. For more information, visit www.spdji.com.
S&P Global is an equal opportunity employer committed to making all employment decisions without regard to race/ethnicity, gender, pregnancy, gender identity or expression, color, creed, religion, national origin, age, disability, marital status (including domestic partnerships and civil unions), sexual orientation, military veteran status, unemployment status, or any other basis prohibited by federal, state or local law. Only electronic job submissions will be considered for employment.