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Data Scientist
Ref No.: 18-02640
Location: New York, New York
Position Type:Full Time
Pay Rate : $ 150,000.00 - 170,000.00 /Year
Global Financial Services Client
Data Scientist
$150K-$170K + bonus
Downtown, NYC

Key Responsibilities
  1. Develop Machine Learning/Statistical Models and Algorithms
  2. Work with business units to translate business problems into actionable tools, insights, and models
  3. Understand ETL process and work with it to transform data to a form that is usable by models leveraging Relational databases, Document Databases, Key-Value DBs, Time Series databases, etc.
  4. Build automated analytics reporting in response to needs from stakeholders across the businesses
  5. Experiment with emerging technologies related to Big Data initiatives for the Data Warehouse platform
  6. Ownership of the various components of the Data Science Life Cycle:  e.g., Data Wrangling, Feature Engineering, Data Visualization (discovery), Model Generation
Qualifications and Experience
  1. Experience solving problems using statistical and quantitative tools
  2. PhD in a quantitative field (e.g. Computer Science, Statistics, Economics, Physics, Mathematics, Operations Research or other quantitative disciplines)
  3. Experience with big data platforms a plus, e.g., Google Cloud Platform, BigQuery, AWS Cloud (S3, EC2, EMR, Redshift, etc.) or Cloudera/Hadoop, or Massively Parallelized DB and/or implemented machine learning/modeling in a real-world situation
  4. Must code and understand, construct and execute SQL queries.  Must have strong expertise with one or more or all of the following:  Python, Python Client Libraries, R, Spark, Mallet, VW, Weka, GraphLab, Scalable Client, TensorFlow, Deep Learning or other Client libraries and tools
  5. Machine Learning or Modelling Experience in one or more of the following:  NLP, Topic Modelling, Image Recognition, Deep Learning, Time Series, Logistic Regression, Random Forest, Neural Nets, (RNN, CNN), AE, Probabilistic Models:  GMM, Bayes NP, RBM, Ensemble Models, Decision Trees, Boosting, Reinforcement Learning, Optimization
  6. Team player who wants to both teach others and learn from others
  7. Passionate about Data, Machine Learning and Engineering
  8. Strong interest in solving business problems