PRISM+ is the largest Singaporean direct-to-consmer smart home appliances brand. Our mission is to offer cutting-edge products to the masses at affordable prices. We are a rapidly growing, ever-evolving organisation, and we are seeking new teammates to join us on our exciting journey.
Responsibilities:
- Analyze large, complex datasets to identify trends, patterns, and correlations that provide valuable insights into business performance and customer behavior. Utilize statistical methods and machine learning techniques to extract meaningful information from data.
- Develop and deploy predictive models to forecast key business metrics, such as customer lifetime value, demand forecasting, and resource requirements. Continuously refine and improve models based on performance evaluation and feedback.
- Identify relevant features and variables that influence the outcome of predictive models. Conduct feature engineering to extract and transform raw data into actionable insights. Apply techniques for feature selection and dimensionality reduction to enhance model performance.
- Evaluate the performance of predictive models using appropriate metrics and validation techniques. Conduct rigorous testing and validation to ensure the accuracy, reliability, and generalizability of models across different datasets and scenarios.
- Communicate findings and insights effectively through data visualization techniques, such as charts, graphs, and dashboards. Translate complex analysis results into clear and actionable recommendations for stakeholders.
- Collaborate closely with cross-functional teams, including software developers, business analysts, and stakeholders, to understand business requirements, define success criteria, and integrate analytical solutions into business processes.
- Stay abreast of emerging trends, technologies, and methodologies in data science, machine learning, and related fields. Experiment with new techniques and tools to enhance analytical capabilities and drive innovation within the organization.
- Proven experience as a Data Scientist, with a strong track record of developing and deploying predictive models in real-world applications.
- Proficiency in programming languages such as Python or R, with experience in data manipulation and analysis libraries (e.g., Pandas, NumPy, scikit-learn).
- Solid understanding of statistical concepts, machine learning algorithms, and data mining techniques.
- Experience with data visualization tools (e.g., Matplotlib, Seaborn, Tableau) and proficiency in communicating complex analysis results to non-technical stakeholders.
- Strong problem-solving skills and analytical thinking, with the ability to translate business questions into data-driven solutions.
- Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams and interact with stakeholders at all levels of the organization.
