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Machine Learning Associate
Ref No.: 17-10714
Location: New York, New York
Position Type:Contract
Start Date: 11/06/2017
Title: Machine Learning / AI Developer
Location: New York, NY or Boston, MA
Duration: 6+ Month Contract/Ongoing

Rate: DOE

  • 5+ years of professional/industry experience in machine learning, mathematical modeling, statistical modeling, optimization or data mining on real world problems involving large data sets - ideally in financial services related industry (e.g., banking and securities, asset management, insurance)
  • At least 2 years of experience with current data visualization applications/tools
  • A track record of academic excellence including a Master's or PhD degree from a reputable college/university in a quantitative field such as statistics, math, applied mathematics, financial mathematics, computational finance, finance, economics, econometrics, operations research, engineering, machine learning, computer science, system engineering, econophysics, physics, or another highly quantitative field
  • CFA, PRM, or FRM designation or candidate
  • Solid MS Office skills - Excel (including macros and VBA) and Access (or SQL), storyboarding and PowerPoint at high proficiency preferred
  • Required: R, Python and/or Tensorflow
  • Desired: Java, PHP, J#.Net environment, Perl, Mathematica, MATLAB, Hadoop, Spark, SAS, STATA, SPSS, RapidMinder, S-plus, ARC-GIS, Weka, NetLogo, MASON, RePast; experience using other programming and data manipulation languages (SQL, Hive, Pig, C/C++)
  • Knowledge of any one visualization tool such as Tableau, Spotfire, PowerView, QlikView, D3.js or equivalent
  • Experience in developing advanced models such as multivariate regression, neural networks, support vector machines, Random Forest, Bayesian Analysis, decision trees, ANOVA and clustering/segmentation
  • Applied Machine Learning modeling expertise is required
  • A background in Deep Learning (CNN, LSTM), Natural Language Processing (Word2Vec), and Anomaly Detection is highly preferred
  • Modeling expertise in Quantitative Modelling, Quantitative Research, Statistics, Predictive Analytics/Predictive Modelling, Algorithmic Engineering, Non-parametric models, Time-series models, Non-linear dynamics, Complexity science, Text mining, Clustering, Monte Carlo and bootstrapping, Supervised and Unsupervised learning methods, Decision Trees and CART, Data Visualization or Data Mining is desirable
  • Working knowledge of Generally Accepted Accounting Principles (GAAP), Basel III, Dodd-Frank Act Stress Testing, and bank accounting/regulatory reporting requirements
  • Ability to travel up to 50-75%
If interested and qualified, please send updated resume in word format to