Data Scientist — Marketing Analytics & AI (Hybrid)

Experian; Malaysia; Híbrido; MYR 90 000 - 140 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Discretionary bonus

Hybrid work arrangement

Equal opportunities employer

Resumo da oferta

Experian is seeking an intermediate Data Scientist to join the Data Science team on a 12-month contract. You will work across data products and analytics initiatives, applying statistics, experimentation and ML to real business problems within a multidisciplinary scrum team.

You'll report to the Data Science and Engineering Manager and collaborate with Product, Data Engineering and other stakeholders to deliver practical analytical outcomes.

Qualificações

• Five years of experience applying data science and ML to business or product challenges.
• Proficiency in Python and SQL for analyzing large datasets.
• Strong knowledge of statistics, experimentation and ML, including regression and design.
• Experience with modern cloud data platforms, such as Snowflake.
• Clear communication and collaboration across multidisciplinary teams.

Responsabilidades

• Analyse complex datasets to identify patterns and insights for decisions.
• Develop and evaluate statistical and machine-learning models with data prep and validation.
• Design experiments using regression, hypothesis testing and A/B testing.
• Collaborate with Product, Data Engineering and stakeholders to translate requirements into solutions.
• Communicate findings clearly to technical and non-technical audiences.

Conhecimentos

Python

SQL

Statistics

Machine Learning

Experimentation

Ferramentas

Snowflake

Descrição da oferta de emprego

Experian is seeking an intermediate Data Scientist to join the Data Science team on a 12-month contract. You will work across data products and analytics initiatives, applying statistics, experimentation and ML to real business problems within a multidisciplinary scrum team.

You'll report to the Data Science and Engineering Manager and collaborate with Product, Data Engineering and other stakeholders to deliver practical analytical outcomes.