Machine Learning Engineer

Short Description

Hands-on experience running in running various methods like Regression, Random forest, k-NN, k-Means, boosted trees, SVM, Neural Network, text mining, NLP, statistical modelling, data mining, exploratory data analysis, statistics (hypothesis testing, descriptive statistics)

Job Description

Key Accountabilities
  • Support delivery of one or more data science use cases, leading on data discovery and model building activities
  • Conceptualize and quickly build POC on new product ideas - should be willing to work as an individual contributor
  • Open to learn, implement newer tools\products
  • Experiment & identify best methods echniques, algorithms for analytical problems
  • Operationalize  Work closely with the engineering, infrastructure, service management and business teams to operationalize use cases
  • Stakeholder Management and Leadership
  • Mentor and guide junior machine learning colleagues
  • Liaise and work closely with business areas, product owners, project managers, business and data analysts
  • Communicate results and key findings to the stakeholders in a clear, consistent and business friendly manner
  • Decision-making and Problem Solving
  • Should be able to look at problems from different dimensions and use judgement based on past experiences, market research, industry specific solutions to choose the right approach for building data products
  • Should be able to decide and look for alternatives if the current approach does not work

Risk and Control Objective
All Barclays colleagues have to ensure that all activities and duties are carried out in full compliance with regulatory requirements, Enterprise Risk Management Framework and internal Barclays Policies and Policy Standards

Education
  • Masters degree or PhD in statistics, mathematics, computer science or related scientific disciplines.
  • Relevant work experience in some or all of the skills below

Technical skills
  • Working experience with large data sets in order to extract business insights or build predictive models
  • Broad knowledge of applied mathematics (probability or statistics, linear algebra)
  • Proficiency in one or more statistical tools/languages Python, Scala, R or SAS and related packages like Pandas, SciPy/Scikit-learn, NumPy etc.
  • Hands on experience and understanding of Big Data ecosystem with technologies like Spark/PySpark, MapReduce, Kafka, Hive etc. with unix scripting. Knowledge around NoSQL technologies would be an added advantage.
  • Hands-on experience running in running various methods like Regression, Random forest, k-NN, k-Means, boosted trees, SVM, Neural Network, text mining, NLP, statistical modelling, data mining, exploratory data analysis, statistics (hypothesis testing, descriptive statistics)
  • Hands of experience and knowledge around feature engineering, dimension reduction and model optimization using gradient decent, PCA etc.
  • Industry experience in building and operationalizing various machine and deep learning models in finance/other domain would be an added advantage

Soft Skills
  • Ability to work with a wide range of stakeholders and convert abstract ideas into actionable requirements
  • Ability to work with ambiguous situations and uncertainty
  • Out of the box thinking to solve real world problems
  • Should be able to juggle between multiple priorities efficiently
  • Work collaboratively with teams across different geographic locations and contribute to Machine Learning capability.
  • Good presentation skills  Should be able to present findings and insights in a manner understandable to business.
  • The Benefits: Our customers deserve the best. The same goes for our employees. That's why at Barclays you'll receive a range of benefits that include a competitive salary and all the tools, technology and support you need to succeed.
  • Our Culture: Everything we do is shaped by the five values of Respect, Integrity, Service, Excellence and Stewardship. The values inform the foundations of our relationships with customers and clients, but they also shape how we measure and reward the performance of our employees. Simply put, success is not just about what you achieve, but about how you achieve it.
  • Dynamic working gives everyone at Barclays the opportunity to integrate professional and personal lives, if you have a need for flexibility then please discuss this with the hiring manager.
  • Barclays is an equal opportunity employer and are opposed to discrimination on any grounds. For more detailed information, please visit our dedicated Diversity and Inclusion site here.

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

Machine Learning Engineer
Associate Banking | Financial Services Full-time Information Technology | Engineering Python | NLP
If you‚??re thinking about moving forward in your career, you should think about moving to Barclays. 

Everything we do at Barclays starts and ends with helping people move forward in their lives. From helping them move forward in the digital age through Digital Eagles, to getting them started in their first home with one of our mortgages. From helping them realise their business dreams through to supporting young people as they make their first, sure move into the adult world through Life Skills. Whatever the future holds, we want to be there for our customers every step of the way.

In a constantly changing, more complex and closely connected world, we‚??re working together to help our customers tackle the challenges of today and prepare for the future. We embrace data, innovation and every possibility the digital world presents. We think creatively about new services, new products and new ways to deliver existing products and services. We believe in listening to and really understanding our customers so that we can give them the best possible help.  

Our attitude, our shared characteristics, our focus and our determination should make us the first and lasting choice for our customers. If you‚??re looking for a career full of excitement, challenge, purpose and opportunity, we should be your first choice.  

Find out how we could help you move forward with your career. 

Please do not share your personal data with us publicly via LinkedIn, we won't ever ask you to. Our Social Media Terms & conditions are available on our website.