Data Scientist Data Scientist

Data Scientist

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posted by July 2, 2018

New York, NY Posted 3 weeks ago eClerx Job description Data Scientist – AI eClerx is looking for a mid-level data scientist who has... Data Scientist


Job description

Data Scientist – AI

eClerx is looking for a mid-level data scientist who has the passion and capability to respond to business questions using customer and operations data, advanced analytics and data science techniques and tools. You will play a critical role in the Brokerage Operations’ Data Science & Analytics team to help shape the data science and execute on key foundational projects.


  • You will work alongside a strong, global team of individuals with diverse backgrounds and skills in analytics and data science
  • You will have the opportunity to directly influence strategic decisions by leading initiatives that drive scale, efficiency, and insight across our organization
  • You will collaborate with business and technology partners to evaluate data sources, techniques, and tools to grow and develop the data science practice

Experience Required:

  • 3-6 years of experience in designing, developing, validating, and deploying predictive models that directly support business decision making
  • Degree in Engineering, Computer Science, Computational Statistics, Operations Research or other quantitative fields
  • Extensive experience with advanced Machine Learning techniques including neural networks, deep learning, reinforcement learning, support vector machines, principal component analysis, regression, time series analysis and clustering
  • Experience in projects involving large scale-multi dimensional databases, complex business infrastructure, and cross-functional teams
  • Strong verbal/written communication and presentation skills, including an ability to effectively communicate with both business and technical team
  • Experience using mainstream languages, such as Python, R, or equivalent to the source, cleanse, and model large data sets
  • Experience visualizing and communicating data using packages such as d3.js, Shiny, and Seaborn, or tools such as Tableau and Qlik
  • Hands-on experience applying machine learning techniques using packages such as scikit-learn, TensorFlow, Keras, Theano, and DSSTN
  • Good understanding of sourcing and wrangling data from warehouses, Big Data (e.g. Hadoop, Spark) and other sources using SQL and scripting
  • Discover and verify new opportunities to identify risk, grow business, scale and optimize operations
  • Help Senior Executives to make decisions utilizing the data and analytical skills
  • Helping to structure work, planning new analyses, translating business questions into analytical projects
  • Identifying and ingesting new data sources and performing feature engineering for integration into models

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