Responsibilities
- Collaborate with stakeholders, senior data scientists and cross-functional teams to understand business objectives and requirements.
- Conduct comprehensive data analysis and apply advanced statistical techniques to identify patterns, trends, and extract insights from large and complex datasets.
- Create visually appealing and insightful data visualizations to communicate complex findings and insights to both technical and non-technical stakeholders.
- Develop and maintain scalable data pipelines and workflows to process and analyse large volumes of data.
- Develop, validate, and maintain predictive models and algorithms tailored to specific business use cases such as customer segmentation and propensity models.
- Contribute to the design and implementation of experiments to test hypotheses and validate model performance.
- Work closely with machine learning engineers to deploy models into production and monitor their performance, providing insights and recommendations for optimization.
- Document methodologies, procedures, and findings in a clear and concise manner to ensure knowledge sharing and maintain accurate records.
- Stay abreast of emerging trends and advancements in data science and machine learning.
Requirements:
- Bachelor’s degree or above in Statistics, Computer Science, Mathematics, Business Analytics, Economics, or Similar or Masters in Statistics or any quantitative analytics or equivalent professional qualification.
- 4-7 years of experience in data science or a related field.
- Knowledge of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.)
- Proficiency in statistical analysis, quantitative analytics, forecasting/predictive analytics, multivariate testing, and algorithm development.
- Strong programming skills in Python, R, SQL, or other programming languages.
- Deep understanding of statistical concepts and techniques, with experience applying them to real-world problems.
- Ability to visualize data, identify trends, and provide sound insights/ suggestions to internal stakeholders.
- Experience in the financial and insurance sector will be advantageous.
- Experience with cloud technologies is ideal (AWS/GCP/Azure etc.)
- Eagerness to learn and adapt to new technologies and methodologies.
- Understanding of Generative AI methodologies, including Retrieval-Augmented Generation (RAG), re-ranker, vector databases, etc.
Company Reg No.: 201131609D | License No.: 24S2411 |EA Personnel: R1655133 - Ashraf | Febrianto
