We are seeking an experienced Database Analyst to join our team in New Zealand. In this role, you will be responsible for turning complex data into actionable insights; helping us and our clients better understand audiences, measure impact, and optimize every brand interaction. You will work closely with customers, internal development teams, and third-party partners to ensure successful delivery of solutions.

Key Job Responsibilities

   Deeply engage with the business needs of major real estate companies and financial loan institutions, leading data source integration and evaluation;

   By leveraging SQL and big data components to explore the client's database, we conducted data quality validation, metadata organization, and business terminology confirmation to ensure the effectiveness and completeness of the analytical foundation.

   Responsible for cleaning, integrating, and preprocessing massive data in the fields of real estate and finance, using SQL, Python, and professional ETL tools to complete operations such as customer feature extraction, transaction flow statistics, and macro data fusion;

   Based on the customer's business pain points, carry out feature engineering work such as feature derivation, binning, and coding conversion to build high-value data indicator assets.

   Build machine learning models such as logistic regression and XGBoost based on preprocessed data for scenarios such as predicting home purchase intention, assessing loan default risk, and grading existing customer value;

   Undertake data support and feature optimization work during the modeling process, ensuring the reproducibility and business interpretability of model results, and efficiently delivering analysis projects.

   Engineering encapsulation of complex analysis logic and model results, customized development of professional data analysis tools and decision support systems for Party A clients.

   Responsible for defining data output interfaces, establishing scoring threshold rules, ensuring that analysis results can be seamlessly embedded into the customer's business flow, and providing stable data decision-making basis for Party A.

   Responsible for data link operation and maintenance of delivered systems, monitoring data synchronization delays and task anomalies;

 

Candidate Requirements

   Bachelor’s degree in Computer Science, Information Systems Mathematics, Financial Engineering or related field — or equivalent experience.

   Minimum 3 years of experience in a data-related role such as Database Analyst, Data Engineer, or Data Scientist.

   Proficient in Python for data cleaning, feature engineering, automation, and model development.

   Advanced SQL skills for complex queries, performance tuning, data validation, and metadata organization.

   Hands-on experience in building machine learning models such as logistic regression and XGBoost for business scenarios like risk assessment, customer scoring, or purchase intention prediction.

   Experience exploring client-side or third-party databases to understand data structure, completeness, and business logic.

   Strong ability to explain technical and model results to non-technical teams (creative, strategy, business operations, and client relationship teams).

   Ability to work directly with clients (real estate companies, financial institutions) to understand business needs and translate them into analytical tasks.