Data Analyst - Revenue and Pricing

Job ID
R18820
Country
France
Job City
Paris
Job Family
Data analysis
Job Type
Employee
Job Sub Type
Permanent

Key Responsibilities:

Data Analysis and Pricing Models:

  • Develop, maintain, and improve pricing models based on large datasets and financial metrics.
  • Conduct detailed analysis of market trends, customer data, and financial metrics to inform pricing decisions.
  • Provide insights into the impact of pricing strategies on revenue, customer retention, and profitability - .

Financial Reporting & Forecasting:

  • Generate financial reports related to pricing strategies, including revenue forecasting and cost analysis, supporting budget processes.
  • Communicate findings to senior management and provide actionable recommendations.

Collaboration with Internal Teams:

  • Work closely with product, finance, and sales teams to align pricing strategies with overall business objectives.
  • Ensure pricing structures comply with regulatory standards and risk management protocols.

Automation & Process Improvement:

  • Support the implementation of pricing automation tools and technologies to enhance efficiency and accuracy.
  • Identify areas for process improvement and help develop innovative pricing models and strategies.

Required Skills & Qualifications:

  • Educational Background:
    Bachelor's degree in Finance, Economics, Data Science, Mathematics, or a related field preferrable. A Master’s degree or professional certification (e.g., CFA, FRM) is a plus.
  • Technical Skills:
    • Proficiency in Excel is essential and in data analytics tools and programming languages such as Python, SQL, and Power BI is a distinct advantage.
    • Experience with pricing strategies.
    • Previous experience with financial metrics.
  • Experience:
    • Preferred minimum of 2 years of experience in a data analytics, financial analysis, or pricing role, preferably within the financial services sector.
  • Analytical & Communication Skills:
    • Strong analytical thinking with attention to detail.
    • Ability to interpret complex datasets and present findings clearly to non-technical stakeholders.
    • Fluency in English is essential, with French or Portuguese an advantage; an with good written and verbal communication skills