Machine Learning Engineer
Grade : BA4
Involvement into multiple use cases to solve business problemsusing machine learning and to meet success criteria defined by business
Ability to convert a business problem into a data science problem
Strong in solving business problems using classification andregression machine learning techniques
Good working knowledge in Logistic Regression, Decision Tree,Random Forest, GBT, XGBOOST, Support Vector Machine, Linear Regression
Should have good exposure and understanding in time seriesModelling using ARIMA, ARIMAX
Exposure into how to handle underfitting and overfitting
Should be capable of applying techniques which helps to generalizeModels
Regularization techniques LASSO, RIDGE & ELASTIC NET and whento apply these
Strong in various feature engineering techniques and when and howto apply these
Good exposure inUnsupervised machine learning like clustering, dimensionality reduction,Outlier detection
Ability to understand how Models are optimized using varioustechniques including Gradient Descent approach
Good understanding of deep learning algorithms CNN, RNN, LSTM andhow to control overfitting in such cases
Relevant years of experience in data science or postgraduate inanalytics / machine learning and demonstrated machinelearning application to multiple use cases using Python
Strong in supervised & un-supervised machine learning. Wellversed with classification type of problems using Random Forest, GradientBoosted Trees, XGBOOST, SVM, logistic regression
Should have worked on regression technique like linear regression.Also sound understanding of various regularization techniques such as LASSO,RIDGE & ELASTIC NET & Time Series Modelling.
Should have sound understanding of various generalizationtechniques like Ensemble, stacking
Shouldhave core machine learning skills like supervised and unsupervised using Pythonand on Spark cluster (using pySpark).
Goodknowledge on time series modelling knowledge like ARIMA, stationarity test etc.
Shouldhave sound understanding of deep learning using KERAS & Tensorflow
Abilityto solve multivariate time series problems
Barclaysis a transatlantic consumer, corporate and investment bank offering productsand services across personal, corporate and investment banking, credit cardsand wealth management, with a strong presence in our two home markets of the UKand the US.
Our goal is to become the bank of choice by providing superiorservices to customers and clients and supporting our stakeholders via acommercially successful business that generates long-
term sustainable returns.
For further information on EVP, please click on thelink below
Riskand Control Objective
AllBarclay’s colleagues have to ensure that all activities and duties are carriedout in full compliance with regulatory requirements, Enterprise Wide RiskManagement Framework and internal Barclays Policies and Policy Standards.
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Barclays Values & Diversity
Dynamic working gives everyone at Barclaysthe opportunity to integrate professional and personal lives, if you have aneed for flexibility then please discuss this with the hiring manager.
Weare an equal opportunity employer and we are opposed to discrimination on anygrounds. It is the policy of Barclays to ensure equal employment opportunitywithout discrimination or harassment on the basis of race, colour, creed,religion, national origin, alienage or citizenship status, age, sex, sexualorientation, gender identity or expression, marital or domestic / civilpartnership status, disability, veteran status, genetic information, or anyother basis protected by law.
Barclaysrecently announced the creation of a new world-class campus at Gera Commerzonelocated in Kharadi. All Pune based roles will eventually start to move to thisnew campus starting September 2019.
In the run up to that, during the course of2018, there may be transitory movements of some roles to other temporary sites.
Please speak with your recruiter about the specific location plans for yourrole.