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Finanice & Risk - Lead Data Scientist / Data Scientist

Job Location: Location Negotiable

Job Number: 00656650

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- Job description

To support building data and analytics practice assets and support go-to-market strategy on data and analytics developments in the financial services market.
The functional coverage of this consulting practice extends across financial services’ risk and regulatory frameworks, predictive modelling, finance processes, risk transformation, risk and regulatory remediation, optimizing risk and regulation implementation and ongoing adherence and delivering end to end solutions required to enable insights through analytics.
Basic qualifications:
Skills and qualifications:
  • Good understanding of hypothesis testing and of statistical tests for significance.
  • Deep hands on handling unstructured data such as digital footprints, keywords, browsing history and behavior and applied on model development    
  • Understanding of univariate, multivariate & time series analysis.
  • Understanding of Bayesian and probabilistic models. 
  • Hand-on in machine learning supervised techniques like regression, classification, decision trees, ensemble algorithms (boosted trees) and random forests etc.
  • Good understanding of unsupervised algorithms clustering, dimensionality reduction, Boltzmann machines (GBM), RBM etc.
  • Some knowledge of Deep neural networks like ANN, CNN, LSTM’s, Seq2Seq, GAN’s, Word Vectors etc.
  • Knowledge of Tensorflow, Pytorch, Keras etc.
  • Nice to have some basic understanding of reinforcement learning like DQN, A3C etc.
  • Deep hands on experience in one or more of these data science toolkits, such as R, Python, Spark, Weka, NumPy, MatLab, etc.
  • Experience with data visualization tools, such as D3.js, GGplot, Tableau, Qlikview etc.
  • Proficiency in using query languages such as SQL, Hive etc.
  • Good to have some experience with NoSQL databases
  • Some basic understanding of handling unstructured data in form of text, speech, pictures and video’s
 
 
Education qualifications:
  • Bachelor’s degree in either Mathematics, Statistics, Data Science, Computer Science or any related discipline
  • Overall 6 years of experience as data scientist in industry.
  • 2+ years of experience in applying data science on Financial domain.
 
Preferred qualifications:
  • At least 6 years of experience in delivery of data analytics in house or consulting services; with proven track record as an individual contributor
  • Credit risk model development using alternate data- digital data, 3rd party data or any unstructured data
  • A good Kaggle ranking/KDD cup ranking would give you a great advantage.
  • Involvement in end to end analytic project which includes ingestion, advance analytic and visualization
  • Diverse background that includes working within different business models and markets
 
 

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