About the job
SummaryBy Outscal
Join Barclays as a Data Scientist and leverage cutting-edge technology to drive innovation and deliver exceptional customer experiences. You'll be responsible for data analysis, model development, and insights extraction using machine learning and cloud technologies like AWS, Snowflake, and Databricks.
About the job
Join us as a Data Scientist at Barclays where you'll spearhead the evolution of our digital landscape, driving innovation and excellence. You'll harness cutting-edge technology to revolutionise our digital offerings, ensuring unapparelled customer experiences.
You may be assessed on the key critical skills relevant for success in role, such as:
Barclays is required by law to confirm that you have the Legal Right to Work in any role that you apply for. If you currently hold a work visa sponsored by Barclays, or you would require sponsorship from Barclays, you must declare this as part of your application. Sponsored visas are role and entity specific and any changes must be reviewed. It is important that you ensure you are working on the correct visa at all times. Failure to accurately disclose your visa status or Legal Right to Work may result in your application or any employment offer being withdrawn at any time.
Purpose of the role
To use innovative data analytics and machine learning techniques to extract valuable insights from the bank's data reserves, leveraging these insights to inform strategic decision-making, improve operational efficiency, and drive innovation across the organisation.
Accountabilities
You may be assessed on the key critical skills relevant for success in role, such as:
- Deep understanding of machine learning and data mining principles, tools and processes
- Deep expertise in Latest Cloud Technology in AWS (Good to have Snowflake, Databricks) including familiarity with Gen AI implementation (Hugging Face, Bedrock, Snowpark)
- Onprem, cloud and hybrid environment experience for building and deploying batch and real-time ML models
- Deep expertise in E2E Machine Learning Model Development Lifecycle using AWS stack and native services
- Hands of experience and knowledge around feature engineering, dimension reduction and model optimization using gradient decent, PCA etc.
- Hands-on experience in distributed data analytics using Hadoop/Spark, Proficiency in scripting languages (e.g. Python, R etc.), ML frameworks/tools (Scitkit-learn, MLlib, Tensorflow)
- Experience in delivering NLP, OCR, Chatbots solution
- Experience on Timeseries, Optimization, Workforce Management, Forecasting etc.
- Experience and understanding of Big Data ecosystem with technologies like Spark/PySpark, MapReduce, Kafka, Hive etc.
- Experience in UNIX scripting and NoSQL would be an added advantage
- Deep expertise in Latest Cloud Technology in AWS (Good to have Snowflake, Databricks) including familiarity with Gen AI implementation (Hugging Face, Bedrock, Snowpark)
- Hands on experience with Databricks and Snowflake from a model development perspective
- Understand business context, study related data sources, build descriptive statistics and develop machine/deep learning models. Evaluation and finalization of analytical models suitable to the use case is key success metric
- Experience working with large data sets in order to extract business insights or build predictive models
- Broad knowledge of applied mathematics (probability, statistics, linear algebra)
Barclays is required by law to confirm that you have the Legal Right to Work in any role that you apply for. If you currently hold a work visa sponsored by Barclays, or you would require sponsorship from Barclays, you must declare this as part of your application. Sponsored visas are role and entity specific and any changes must be reviewed. It is important that you ensure you are working on the correct visa at all times. Failure to accurately disclose your visa status or Legal Right to Work may result in your application or any employment offer being withdrawn at any time.
Purpose of the role
To use innovative data analytics and machine learning techniques to extract valuable insights from the bank's data reserves, leveraging these insights to inform strategic decision-making, improve operational efficiency, and drive innovation across the organisation.
Accountabilities
- Identification, collection, extraction of data from various sources, including internal and external sources.
- Performing data cleaning, wrangling, and transformation to ensure its quality and suitability for analysis.
- Development and maintenance of efficient data pipelines for automated data acquisition and processing.
- Design and conduct of statistical and machine learning models to analyse patterns, trends, and relationships in the data.
- Development and implementation of predictive models to forecast future outcomes and identify potential risks and opportunities.
- Collaborate with business stakeholders to seek out opportunities to add value from data through Data Science.
- Consult on complex issues; providing advice to People Leaders to support the resolution of escalated issues.
- Identify ways to mitigate risk and developing new policies/procedures in support of the control and governance agenda.
- Take ownership for managing risk and strengthening controls in relation to the work done.
- Perform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub-function.
- Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategy.
- Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practises (in other areas, teams, companies, etc).to solve problems creatively and effectively.
- Communicate complex information. 'Complex' information could include sensitive information or information that is difficult to communicate because of its content or its audience.
- Influence or convince stakeholders to achieve outcomes.
About The Company
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