Data Scientist Analyst

Barclays Business Banking; Northampton; On-site; GBP 45,000 - 75,000; Full time

Job summary

An established industry player is seeking a Data Scientist Analyst to lead the transformation of its digital landscape. This role involves leveraging innovative data analytics and machine learning techniques to extract insights that inform strategic decisions and enhance operational efficiency. You will play a vital role in the Cyber Fraud Fusion Center, utilizing cutting-edge technology to combat fraud and protect customers. If you're passionate about data and eager to drive innovation in a dynamic environment, this opportunity is perfect for you.

Qualifications

• Practical experience in databases, Python, and machine learning.
• Knowledge of statistics and ability to design automated processes.

Responsibilities

• Data collection, cleaning, and integration from various sources.
• Development of predictive models and collaboration with stakeholders.

Skills

Python

Jupyter Notebook

Hadoop

Spark

REST APIs

Machine Learning Algorithms

Statistical Analysis

Data Mining

Critical Thinking

Tools

Quantexa

i2

Palantir

Maltego

Elastic Search

SAS

Tableau

Power BI

Job description

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:

• Minimum requirement: practical experience in relational and non-relational databases, Python, Jupyter Notebook, Hadoop, Spark, and Rest APIs.
• Familiar with 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 type II errors, association analysis, frequent pattern mining, data mining, and critical thinking to build KPIs based on defined problems.
• Knowledge of statistics including probability, confidence intervals, hypothesis testing, central limit theorem, t-test, z-test, chi-square, and ANOVA.
• Ability to design and build automated processes linking various sources and destinations in batch or real-time, including REST APIs, databases, SFTP, and queues.

Additional highly valued skills may include:

• Knowledge of social engineering tactics used by cybercriminals, particularly in scams.
• Basic knowledge of security network architectures and principles of network security.
• Experience with analytical tools/platforms such as Quantexa, i2, Palantir, Maltego, Elastic Search, SAS, Tableau, and Power BI.
• Certifications in machine learning courses.

You may be assessed on key skills such as risk management, controls, change and transformation, business acumen, strategic thinking, digital and technology skills, along with 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 insights from the bank's data, informing strategic decisions, improving operational efficiency, and driving innovation.

Accountabilities:

• Data collection, extraction, and integration from various sources.
• Data cleaning, wrangling, and transformation for quality analysis.
• Development and maintenance of data pipelines for automated processing.
• Design and execution of statistical and machine learning models to analyze data patterns.
• Development of predictive models to forecast outcomes and identify risks and opportunities.
• Collaborate with stakeholders to leverage data science for value addition.

Analyst Expectations:

• Perform activities timely and to high standards, fostering continuous improvement.
• Possess in-depth technical knowledge and experience.
• Lead or contribute technically within the team, guiding development and supporting colleagues.
• Demonstrate leadership behaviours where applicable, or develop technical expertise as an individual contributor.
• Impact related teams and partner across functions.
• Manage risks, controls, and compliance with policies and regulations.
• Understand how their work aligns with organizational objectives and contributes to overall success.
• Make evaluative judgments, resolve problems, and communicate effectively with stakeholders.

All colleagues are expected to embody Barclays Values: Respect, Integrity, Service, Excellence, and Stewardship, and demonstrate the Barclays Mindset: Empower, Challenge, and Drive.