Pricing Data Scientist

2 weeks ago

Singapore Moladin Full time

**Responsibilities**:

- Data Analysis and Modelling:

- Utilize statistical methods to identify key variables influencing pricing and customer behaviour.
- Develop and maintain statistical models for price elasticity, demand forecasting, and other relevant pricing metrics.
- Collaborate with Data Science and Engineering teams to leverage advanced analytics techniques and machine learning algorithms for pricing optimization.
- Pricing Optimization:

- Collaborate with stakeholders to define pricing objectives, guidelines, and policies.
- Evaluate and implement pricing tools and technologies to streamline pricing processes and improve efficiency.
- Conduct scenario analysis and simulations to optimize pricing strategies based on different market conditions and business goals.
- Monitor pricing KPIs and provide actionable insights to drive pricing decisions and revenue growth.
- Used Car Pricing Analysis and Strategy:

- Analyse used car pricing data from various sources, including market trends, competitor prices, and internal historical data.
- Conduct statistical analysis to identify pricing patterns, customer preferences, and pricing opportunities.
- Develop and refine pricing models and algorithms to optimize pricing decisions.
- Collaborate with cross-functional teams, including Sales, Marketing, and Finance, to align pricing strategies with business objectives.
- Monitor pricing performance and recommend adjustments to improve revenue, reduce losses, profit margins, and inventory turnover.

**Requirements**:

- Bachelor's or Master's degree in a quantitative field (e.g., Mathematics, Statistics, Economics, or related disciplines). A strong mathematics background is highly desirable.
- 5+ years of experience in pricing analytics, preferably in the automotive industry (plus).
- Proficiency in classical analytics techniques, including statistical analysis, regression modelling, and data visualization.
- Strong analytical and problem-solving skills, with the ability to analyse complex datasets and draw actionable insights.
- Familiarity with classical data science techniques and tools, such as R or Python, for data manipulation and analysis.
- Understanding of the used car market, pricing dynamics, and customer behaviour in the automotive industry is a plus.
- Excellent communication skills, with the ability to present complex analytical findings to non-technical stakeholders.
- Strong attention to detail, with a focus on data accuracy and reliability.
- Ability to work independently and collaboratively in a fast-paced, dynamic environment.

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