Job Location: Pune
Job Title: Machine Learning Engineer
Barclays is a British universal bank. We are diversified by business, by different types of customers and clients, and by geography. Our businesses include consumer banking and payments operations around the world, as well as a top-tier, full service, global corporate and investment bank, all of which are supported by our service company which provides technology, operations and functional services across the Group.
Risk and Control Objective
Ensure that all activities and duties are carried out in full compliance with regulatory requirements, Enterprise Wide Risk Management Framework and internal Barclays Policies and Policy Standards.
We’re committed to providing a supportive and inclusive culture and environment for you to work in. This environment recognises and supports ways to balance your personal needs, alongside the professional needs of our business. Providing the opportunity for all our employees, globally to work flexibly empowers each of us to work in a way that suits our lives as well as enabling us to better service our customers’ and clients’ needs. Whether you have family commitments or you’re a carer, or whether you need study time or wish to pursue personal interests, our approach to working flexibly is designed to help you balance your life.
If you would like some flexibility then please discuss this with the hiring manager.
As a Machine Learning Engineer you will be involved into various machine learning activities starting from data discovery, exploratory data analysis & solving business problems from an analytics standpoint & using machine learning models as needed. You should also have the capability to take these Models into production with best practices & monitoring model & improving Models further to stay useful to business. This role would require to have data engineering skills using Python & Spark.
What will you be doing?
- Ability to convert a business problem into a data science/machine learning problem
- Strong in solving business problems using classification and regression 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 series Modelling using ARIMA, ARIMAX
- Exposure into how to handle under fitting and overfitting
- Should be capable of applying techniques which helps to generalize Models
- Regularization techniques LASSO, RIDGE & ELASTIC NET and when to apply these
- Strong in various feature engineering techniques and when and how to apply these
- Good exposure in Unsupervised machine learning like clustering, dimensionality reduction, Outlier detection
- Ability to understand how Models are optimized using various techniques including Gradient Descent approach
- Good understanding of deep learning algorithms CNN, RNN, LSTM and how to control overfitting in such cases
- Good hands on in data engineering to process huge scale of data using Big Data (Spark/Hive)
- Good coding practices to write production ready code for creating data pipeline for Models to consume
- Very good hands on in python (Pandas/Numpy/Scikit-Learn/NLTK/spaCy/Matplotlib)
What we’re looking for:
- 4+ years of experience in data science or postgraduate in analytics/machine learning and demonstrated machine learning application to multiple use cases using Python & Spark
- Strong in supervised & un-supervised machine learning. Well versed with classification type of problems using Random Forest, Gradient Boosted 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 generalization techniques like Ensemble, stacking
- Very good hand on in Python (Pandas/Numpy/Scikit-Learn/NLTK/spaCy/Matplotlib)
- Good hand on in data engineering skills using Big Data (Spark/Hive)
- Very good SQL experience & knows how to write optimized queries
Skills that will help you in the role:
- Should have core machine learning skills like supervised and unsupervised using Python and on Spark cluster (using pySpark).
- Good knowledge on time series modelling knowledge like ARIMA, stationarity test etc.
- Should have sound understanding of deep learning using KERAS & Tensorflow
- Good data engineerign skills
- Knowledge of DevOps & Model deployment framework
Where will you be working?
Be More at Barclays
At Barclays, each day is about being more – as a professional, and as a person. ‘Be More @ Barclays’ represents our core promise to all current and future employees. It’s the characteristic that we want to be associated with as an employer, and at the heart of every employee experience. We empower our colleagues to Be More Globally Connected, working on international projects that improve the way millions of customers handle their finances. Be More Inspired by working alongside the most talented people in the industry, and delivering imaginative new solutions that are redefining the future of finance. Be More Impactful by having the opportunity to work on cutting-edge projects, and Be More Valued for who you are.
Interested and want to know more about Barclays? Visit home.barclays/who-we-are/ for more details.
Purpose, Values and Mindset
We deploy finance responsibly to support people and businesses, acting with empathy and integrity, championing innovation and sustainability, for the common good and the long term.
Our values underpin everything we do: Respect, Integrity, Service, Excellence and Stewardship.
We harness the power of diversity and inclusion in our business, trust those we work with, and value everyone’s contribution.
We operate with honesty, transparency and fairness in all we do.
We act with empathy and humility, putting the people and businesses we serve at the centre of what we do.
We champion innovation, and use our energy, expertise and resources to make a positive difference.
We prize sustainability, and are passionate about leaving things better than we found them.
Our Mindset shapes how we take action, living by our Values, driven by our Purpose, always with our customers and clients at the heart of what we do; our Mindset is to Empower, Challenge and Drive.
Trust and support each other to deliver. Make decisions with those closest to the topic. Include diverse perspectives. Celebrate success and learn from failure.
Question whether things can be done better. Use insights based on data to inform decisions. Be curious about how we can adapt and improve. Speak up and be open to alternative viewpoints.
Focus on outcomes. Deliver with pace. Be passionate and ambitious about what we do. Take personal responsibility. Actively build collaborative relationships to get things done.