Barclays
Banking
DecisionAnalyst
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Decision Analyst at Barclays. Skills: Data analytics, Machine learning techniques, Data Science, Statistical models, Predictive models, Data pipelines, Python, SAS, SQL. Identification, collection, extraction of data from various sources. Performing data cleaning, wrangling, and transformation”
What You'll Achieve.
Inform strategic decision-making; Improve operational efficiency; Drive innovation; Ensure unapparelled customer experiences; Drive the best outcome across channels and partners
Industry & Context.
Assess the validity and applicability of previous or similar experiences and evaluate options under circumstances that are not covered by procedures
What They're Looking For.
Must Have
Proficient in Python, SAS, SQL, A good knowledge of data analysis and statistical techniques (such as linear or nonlinear models, logistic regression, macroeconomic forecast, decision trees, cluster analysis and neural networks etc. ), Deep understanding of Cards P&L and forecasting methodologies
Nice to Have
Experience in Credit Card / Banking, Data Science, Machine Learning and Advanced Analytics, Experience with Data visualization
What You'll Do.
extraction of data from various sources
Performing data cleaning
Development and maintenance of efficient data pipelines
Design and conduct of statistical and machine learning models
Development and implementation of predictive models
Collaborate with business stakeholders to seek out opportunities to add value from data through Data Science
Lead and build automated forecasting solutions to valuate acquisition marketing investments
Drive marketing investment optimization decision for the business
Leverage data science capabilities through operationalizing data platform and advance analytical methodologies and tools to forecast P&L
Monitor model accuracy to drive the best outcome across channels and partners
How You'll Work.
Team & Collaboration
Collaborate with business stakeholders; Collaborating with and impacting on the work of closely related teams; Build relationships with stakeholders/ customers to identify and address their needs; Align across the enterprise
Communication Scope
Communicate sensitive or difficult information to customers
Full Job Description
# **Job Description** **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. **Analyst Expectations** * To meet the needs of stakeholders/ customers through specialist advice and support * Perform prescribed activities in a timely manner and to a high standard which will impact both the role itself and surrounding roles. * Likely to have responsibility for specific processes within a team * They may lead and supervise a team, guiding and supporting professional development, allocating work requirements and coordinating team resources. They supervise a team, allocate work requirements and coordinate team resources. * If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others. * OR for an individual contributor, they manage own workload
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