Data Scientist (w/ NLP)

Our client a top-tier Management, Strategy and IT Consulting firm is seeking to bring on a Data Scientist onto their Wholesale and Retail Banking practice to support various consulting projects/efforts with their Financial Services Banking end clients.

The Global Markets Data Analytics team based in New York and Raleigh  have a mission to use big, alternative and directly sourced data to describe and predict key metrics of companies and economies so that we may deliver innovative data solutions and insights to our internal analyst teams and the firm's clients. We are looking for self-starting and innovative senior data scientist to join and grow our team. You must have a keen interest in financial markets and experience with modern analytical tools and methods, including processing data at large scale for analytical purposes, while maintaining proper empirical discipline and rigor.

  • Use Natural Language Processing to develop key models, leveraging various data sources ranging from social and text to quantitative factor modeling
  • Model execution pipeline with model validation, model monitoring, model scoring, model decay and retraining
  • Work with street leading analysts to facilitate their requests for new and innovative data analytics.
  • Help design and construct the data processing and analytics infrastructure necessary to perform advanced analytical research within a global enterprise.
  • Create original insights from data by executing applied empirical research in a timely manner
  • A PhD, or Masters with equivalent work experience, with a solid background in machine learning, statistical analytical techniques, quantitative social science research or experimental physical science.
  • Advanced Knowledge of Python, Scala and Java
  • 3+ years of profession experience and discipline in building Machine Learning models
  • 3+ years of experience in Statistics and Data Science techniques like exploratory analysis, feature engineering and ML techniques like clustering, regressions, classifications etc.
  • Experience with machine learning packages such as NLTK, Spacy, genism, fasttext, TensorFlow, PyTorch, Keras, Scikit-Learn, NumPy, SciPy, Pandas, StatsModels, Spark ML
  • Exposure to Machine Learning techniques like hyper parameter tuning, model validation, model serving, model monitoring, retraining etc. (Machine Learning pipeline)
  • Experience with machine learning lifecycle tools (i.e. mlflow, kubeflow)
  • Excellent written and spoken English, with ability to work collaboratively and communicate well within a highly skilled team, with a wide range of backgrounds and skillsets
Nice to Have Qualification:

  • Relevant hands on work with unclean, semi-structured or unstructured data sets
  • Experience working in teams of analysts, data engineers, statisticians, and data scientists
  • Experience in analytics (a.k.a. decision sciences) in the financial industry;
  • Proficient analytical and math background
  • Demonstrated success in performing within a functional organizational environment
  • Innovative mindset—thinks beyond the status quo
  • Knowledge of BERT, AllenNLP, Spark, Hadoop, H20 and/or cloud computing