Dianzi (Angel) Wang

I’m interested in how AI can support recruitment and informed hiring decisions.

Recruitment experience in China and postgraduate training in data analytics in the UK have shaped the way I assess people, roles and organisational context.

I care about finding a genuine fit between people and roles, using structured approaches and data to make the process more efficient and consistent.

AI for recruitment Evidence-informed candidate assessment Business-focused people decisions Cross-cultural recruitment communication

View projects View CV

A personal photograph of Dianzi (Angel) Wang

Education

Theory → Data → AI

University College London

MSc People Analytics and Human-Centric ManagementAssessments completed; award pending

Sep 2025 – Sep 2026 · London, UK

During my master’s studies, I developed the ability to frame HR questions as problems for data analysis and decision-making.

Through training in R and Python, I learned to structure and analyse HR data and communicate key insights through visualisation, making judgements previously based on experience clearer and more explainable.

Modules in strategic HR management, organisational behaviour, diversity management and leadership also helped me understand people decisions at an organisational level, considering business needs, team structures and organisational context.

Across course projects and case analyses, I examined real business contexts, including recruitment decision support, organisational diagnosis and the redesign of collaboration between people and AI.

This experience helped me develop a more connected analytical approach: using theory to understand people, data to refine judgement and AI to rethink recruitment and organisational decision-making.

Northwest University

Bachelor’s degree in Labour and Social Security

Sep 2020 – Jun 2024 · Xi’an, China

My undergraduate studies provided systematic academic training in HR and labour and social security. Core areas included HR management, personnel assessment and selection, employment relations, compensation and benefits, and social security, giving me a rounded foundation in HR management.

Studying China’s labour market and employment structures also helped me understand talent supply and demand, differences between industries and how organisations employ people. This provided important context for my later recruitment decisions.

I came to see recruitment not as an isolated matching exercise, but as a decision-making process embedded in the wider labour market.

Internship experience

Delivery → Systems → Judgement

ByteDance

Talent Acquisition Intern – Mid-to-Senior Recruitment

Apr 2024 – Jun 2024 · Xi’an, China

At ByteDance, recruiting for mid-to-senior roles brought me face to face with more complex hiring judgements.

Compared with entry-level roles, these positions required a deeper understanding of the business and more demanding candidate criteria. CV information alone was not enough to support an assessment.

I needed to actively build my business knowledge, understand the rationale behind each role and refine assessment criteria through conversations with hiring teams.

Sourcing and speaking with candidates also showed me that mid-to-senior professionals often have more options and tighter time constraints. Recruitment therefore involves strategic communication and relationship-building, not simply screening.

This experience helped me turn experience-based judgements into a more structured analytical process, with greater attention to consistency and explainability.

Tencent

Campus Recruitment Intern

Jul 2023 – Nov 2023 · Shenzhen, China

Tencent’s campus recruitment programme was my first experience of HR operations with highly standardised processes and clearly defined responsibilities.

From sourcing and screening to interview coordination, each stage had clear processes and criteria. I learned that recruitment draws on experience, but can also be broken down, improved and repeated systematically.

Working with large numbers of candidates helped me understand the relationship between process efficiency and assessment quality. I began organising information and decisions more systematically.

The experience also introduced me to more established tools and methods, broadened my understanding of recruitment work and helped me develop my own way of working.

Eclicktech

HR Business Partner Intern

Jan 2023 – Apr 2023 · Xi’an, China

This was my first opportunity to apply my academic HR training in a real business setting.

At a medium-sized internet company, I supported recruitment and gained exposure to business-facing HRBP work, including understanding requirements, communicating with candidates and organising recruitment data.

The flexible team structure allowed me to contribute at several stages. I gradually understood recruitment as a connection between business needs and talent supply, rather than simply a sequence of tasks.

The experience shifted my focus from “How do I complete this recruitment task?” to “Why does the business need this person?”

“

I believe sound hiring judgement draws on more than experience: it means understanding the business, understanding people and analysing data to make better decisions.

PROJECTS

Projects

From research on AI and data skill requirements and advertised pay to business analytics and real-client consulting, I combine theory and evidence to turn analysis into practical insights and decision support.

Featured research · UCL MSc dissertation

AI, Data Skills and Advertised Pay in UK HR Roles

A quantitative content analysis of job advertisements

Are AI and advanced data skill requirements in job advertisements associated with higher advertised pay?

I collected job advertisements through Reed’s official API, screened roles, audited pay and coded recruitment text to build an analysis sample of 2,229 full-time HR advertisements. I then used regression models to compare how the two types of requirement relate to advertised pay.

Skill requirements and advertised pay

Fully adjusted model · Percentage differences and 95% confidence intervals

AI-related requirements

+16.34%Statistically significant

95% CI 6.36%–27.25% · p < .001

Strict Advanced Data requirements

+1.97%Not statistically significant

95% CI -2.99%–7.19% · p = .443

Advertised pay difference (%) · Dashed line: 0%

Points show estimated differences in advertised pay; lines show 95% confidence intervals. Both requirements enter the model together, accounting for job level, HR function, London location, recruitment-agency-related variables, pay basis and posting period.

* Redrawn from the main model results in section 4.2 of the author’s MSc dissertation.

From raw job advertisements to research findings

Data collection and cleaning · Contextual coding of job requirements · Salary standardisation · Statistical modelling and robustness checks

Python
Job advertisement text analysis
Regression modelling
UK HR labour market

Read research overview View dissertation PDF

ORCA Guidebook

Global expansion governance

Real-client consulting project

Governance and Risk for ORCA’s Global Expansion

Consulting with a real business client

As a member of a UCL Practera Applied People Analytics project team, I contributed to a consulting project with a real business client.

Our client, ORCA, was exploring a distributed recycling model for port communities worldwide. It aimed to work with partners across countries and regions to build a global network for recycling fishing nets.

As the project expanded, the challenge went beyond technology: how could partners operate reliably, safely and consistently across different legal systems, cultures and operating conditions?

Consulting Governance design Global operations Risk assessment

My contribution

I was responsible for the Standards & Legal Requirements module. I researched international standards, legal compliance and partner governance, and designed a framework combining global standards, operational standards and local legal requirements.

Project highlights

A UCL Practera real-client consulting project
Collaboration with a real business client
Delivery of the team’s final consulting report
Research into international standards and legal systems
Governance design for global operations

What I learned

This was my first real-client consulting project. Compared with classroom case analysis, it demanded more judgement in complex contexts and a stronger focus on organisational governance, risk control and practical implementation.

View case study →

Store24 Analysis

Retention × Performance

Strategic HR analytics

Employee Tenure and Store Profitability

Talent retention and store performance at Store24

Businesses often assume that lower employee turnover is always better. Using Store24 data, this project examined how manager and employee tenure relate to store profit, seeking evidence for the business value of retention strategies.

Strategic HR management Talent retention Business decisions Data analysis

My contribution

Data and regression analysis, framing the business problem and developing HR strategy recommendations.

Project highlights

Connecting HR with business outcomes
Regression modelling
A business decision-making perspective
Applying strategic HR management

What I learned

I began to understand HR’s value through business outcomes. Managing people is not only an end in itself; it also supports better organisational performance.

View case study →

People Analytics

Prices × Neighbourhood characteristics

People Analytics

Fast-Food Prices and Neighbourhood Characteristics

Statistical analysis in R

Using fast-food industry data from New Jersey and Pennsylvania, this project examined how neighbourhood income, population composition and brand factors relate to price differences. Statistical analysis and modelling turned an observed business phenomenon into questions that could be tested with data.

R Statistical analysis Regression modelling People Analytics

My contribution

Data cleaning, descriptive analysis, hypothesis testing, multiple regression and model interpretation.

Project highlights

Analysis in R
Multiple regression modelling
Hypothesis testing
Evidence-informed decisions

What I learned

I learned to use statistical methods to test real-world questions, rather than relying on experience or intuition alone.

View case study →

Data Visualisation

Understanding user behaviour

Data visualisation

Understanding Online Purchase Conversion

Data visualisation in Python

Using more than 12,000 e-commerce browsing sessions, this project analysed key factors associated with purchase conversion. Visualisations explored browsing behaviour, time on site and visitor type, turning complex data into more accessible business insights.

Python Data visualisation User behaviour analysis Business insight

My contribution

Data preparation, user behaviour analysis, visualisation design and interpretation of insights.

Project highlights

Analysis in Python
Data visualisation design
User behaviour research
Communicating business insights

What I learned

I began to think about how to turn complex data into information managers can quickly understand, so that analysis genuinely supports decisions.

View case study →

Beyond Tools

Tools change, but understanding the business, assessing people and supporting decisions remain essential.

Across recruitment, data analysis and consulting, I focus on turning complex problems into decision-making processes that are understandable, testable and actionable.

Understanding people is still the core of People Analytics.

CAPABILITY

Core skills

I aim to combine HR knowledge, data analysis and practical AI tools to make candidate assessment and business support more efficient and structured.

AI for HR

Putting AI to practical use in recruitment and people management, with usable outputs.

I use AI tools across key recruitment and people-management tasks: supporting recruitment, refining job descriptions, summarising candidate profiles, drafting structured interview questions, analysing employee survey responses and developing HR policy Q&A prototypes.

I also use AI-assisted coding (vibe coding) to build HR project pages and lightweight workflow prototypes, turning ideas into work that can be shown and tested.

AI for recruitment Job description refinement Candidate profiles Structured interviews Employee survey analysis HR policy Q&A AI-assisted coding Workflow prototyping

People Analytics

Using data to answer HR and business questions, not simply produce results.

I can independently carry out data cleaning, descriptive analysis, hypothesis testing, regression analysis and visualisation, primarily using R and Python, with SPSS as a complementary tool.

I focus on translating analytical results into explainable business insights, rather than stopping at charts or code.

R Python SPSS Regression analysis Hypothesis testing Data visualisation Dashboard thinking Business insight

HR foundations

Formal academic training in HR, spanning education in China and the UK.

My undergraduate studies covered HR management, personnel assessment and selection, employment relations, compensation and benefits, and social security, providing a solid theoretical foundation in HR.

At UCL School of Management, my master’s studies focused on People Analytics, strategic HR management, organisational behaviour and data analysis, connecting established HR knowledge with data-informed people decisions.

HR management Personnel assessment Employment relations Strategic HR management Organisational behaviour

HR practice

Experience of the recruitment process in real settings, beyond the concepts.

My recruitment and HRBP internships at internet companies covered campus and mid-to-senior recruitment. I contributed to key stages from talent sourcing and candidate communication to progressing interviews.

I approach role requirements and candidate characteristics through a business lens, so that recruitment connects with what hiring teams actually need.

Campus recruitment Mid-to-senior recruitment HRBP Talent mapping Candidate communication Interview coordination Recruitment data Cross-functional communication

AT A GLANCE

Core strengths at a glance

HR & communication

I have a solid academic foundation in HR and am comfortable communicating across cultures.

English (IELTS 7.5) · Mandarin (native)

Data analysis

R · Python · SPSS

Regression · Hypothesis testing · Data visualisation · People Analytics

China and UK hiring markets

Recruitment internships in China’s internet sector · UK HR labour-market research

An HRBP business perspective · Insights across both markets

AI applications

Prompt design · AI workflow automation

AI-assisted coding · HR prototyping

My focus is not on tools alone, but on combining HR knowledge, data analysis and AI to support clearer, more consistent hiring judgements.

Contact

Emailangelwang529@gmail.com

Phone+44 7344 405782

LocationLondon, UK

LinkedInDianzi (Angel) Wang

WeChatangelwang529

CV

View CV Download CV

Dianzi (Angel) Wang

From HR Theory to Recruitment Practice

Education

University College London

Northwest University

Internship experience

ByteDance

Tencent

Eclicktech

Projects

Skill requirements and advertised pay

From raw job advertisements to research findings

Global expansion governance

Governance and Risk for ORCA’s Global Expansion

My contribution

Project highlights

What I learned

Retention × Performance

Employee Tenure and Store Profitability

My contribution

Project highlights

What I learned

Prices × Neighbourhood characteristics

Fast-Food Prices and Neighbourhood Characteristics

My contribution

Project highlights

What I learned

Understanding user behaviour

Understanding Online Purchase Conversion

My contribution

Project highlights

What I learned

Beyond Tools

Core skills

AI for HR

People Analytics

HR foundations

HR practice

Core strengths at a glance

HR & communication

Data analysis

China and UK hiring markets

AI applications

Contact

CV