Join us as a Data Scientist Analyst 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 unparalleled customer experiences. In this role, you will be an integral part of our Cyber Fraud Fusion Center, delivering scalable CFFC services to disrupt fraud and protect our customers and clients from economic crime.
To be successful as a Data Scientist Analyst, you will need the following:
1. Minimum requirement: practical experience in relational and non-relational databases, Python, Jupyter Notebook, Hadoop, Spark, and REST APIs.
2. Knowledge of descriptive and prescriptive analysis, understanding data and distribution, machine learning algorithms such as regression, clustering, bagging, boosting, neural networks, confusion matrix, ROC-AUC curve, type I and II errors, association analysis, frequent pattern mining, data mining, and critical thinking to build KPIs based on defined problems.
3. Statistics: probability, confidence intervals, hypothesis testing, central limit theorem, t-test, z-test, chi-square, and ANOVA.
4. Ability to design and build automated processes linking various sources and destinations in batch or real-time, including REST APIs, databases, SFTP, and queues.
Some other highly valued skills may include:
1. Knowledge of social engineering tactics used by cybercriminals, especially in scams.
2. Basic knowledge of security network architectures (e.g., proxies, VPN, DNS, web, and mail servers) and principles of network security.
3. Experience with analytical tools and platforms such as Quantexa, i2, Palantir, Maltego, Elastic Search, SAS, and MI tools like Tableau and Power BI.
4. Certifications in Machine Learning courses.
You may be assessed on key skills such as risk and controls, change and transformation, business acumen, strategic thinking, digital and technology skills, and job-specific technical skills.
The successful candidate will be based in Knutsford or Northampton.
Purpose of the role
To use innovative data analytics and machine learning techniques to extract valuable insights from the bank's data reserves, informing strategic decisions, improving operational efficiency, and driving innovation.
Accountabilities
* Data identification, collection, extraction from various sources.
* Data cleaning, wrangling, and transformation.
* Development and maintenance of data pipelines.
* Design and conduct of statistical and machine learning models.
* Development and implementation of predictive models.
* Collaborate with stakeholders to add value from data through Data Science.
Analyst Expectations
* Perform activities timely and to high standards, driving continuous improvement.
* Require in-depth technical knowledge and experience.
* Lead and support team development, or develop technical expertise as an individual contributor.
* Impact related teams and partner with other functions.
* Manage risk, embed policies, influence decision-making, and ensure controls.
All colleagues are expected to demonstrate Barclays Values and Mindset, fostering an environment of respect, integrity, service, excellence, and stewardship.
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