Commercial & Financial Modelling Analyst

Sei unter den ersten Bewerbenden.
Nur für registrierte Mitglieder
Genf
CHF 80’000 - 120’000
Sei unter den ersten Bewerbenden.
Vor 2 Tagen
Jobbeschreibung

Our client is an established Oil trading company, with physical assets across Europe. They actively source, refine, market and trade Crude Oil and Oil products, and associated financial derivatives.

We are seeking a highly analytical and commercially minded professional to support the financial and strategic decision-making processes across the Group. The successful candidate will play a critical role in delivering robust financial and quantitative analysis, supporting management reporting, and providing insights that inform both operational and investment strategies.

RESPONSIBILITIES:

  • Develop, enhance and maintain financial models that support strategic decision-making – from daily operations to long-term investments and acquisitions. This includes improving existing methodologies and leveraging tools such as Excel, R & SQL.
  • Work closely with key business units including Refinery Planning, Economics & Scheduling, Finance, Risk, M&A and Corporate Finance. Deliver insightful quantitative analysis to support their operational and strategic objectives.
  • Prepare detailed financial and performance reports for senior management, including analysis of trading and hedging performance against forecasts, leveraging forward derivative market data and P&L projections.
  • Build and maintain models for EBITDA, GRM and cash flow forecasts for the refinery business. Support financial planning for major events including bond issuances, inventory refinancing, factoring facilities and dividend distributions etc.
  • Evaluate potential investments through rigorous financial and commercial due diligence. Prepare pro-forma financial statements (P&L, balance sheet and cashflow) for decision support on an ad-hoc basis.
  • Conduct in-depth analysis on refinery-related projects, including margin and FX risk assessments, working capital management and financing, liquidity forecasting, covenant analysis and economic feasibility reviews of initiatives and projects under management consideration.

COMMERCIAL SKILLS:

  • Strong analytical mindset with proven business acumen.
  • Comfortable with financial, trade and management reporting analysis.
  • Solid foundation in statistical analysis and accounting principles.
  • Highly numerate with strong attention to detail.
  • Strong verbal and written communication skills, capable of conveying complex concepts to all levels in the organization.
  • Confident in influencing stakeholders and building cross-functional consensus.
  • Excellent presentation capabilities, both in content development and delivery.
  • Fluency in English required; proficiency in French, Danish or German is advantageous.
  • Adaptable and effective in fast-paced environments; able to prioritise and resolve issues independently.
  • Self-motivated and performance driven, with leadership ambition.
  • Comfortable moving from strategic concept development to hands-on execution.
  • Collaborative team player with excellent interpersonal and relationship building skills.

QUALIFICATIONS, TECHNICAL SKILLS AND EXPERIENCE:

  • Degree in Finance, Economics, Mathematics, Engineering or a related quantitative field.
  • Experience in building and maintaining complex models using tools such as Excel, R and SQL.
  • Hands-on involvement in delivering complex, multi-disciplinary modelling projects, including the development of neural network models.
  • Practical application of AI/ML techniques in industrial process optimisation and predictive analytics
  • Demonstrated ability to take on divers roles across the lifecycle of complex modelling initiatives including:
  • Product ownership – defining vision, roadmap and stakeholder alignment,
  • Project management – planning, coordination and execution of modelling initiatives,
  • Requirements analysis and specification – gathering business needs and translating them into technical requirements,
  • Solution design – architecting robust analytical frameworks and methodologies,
  • Model generation – coding, testing and validating statistical or machine learning models,
  • User acceptance testing – managing end-user testing and feedback integration, and
  • On-going support and maintenance – ensuring reliability, scalability and continuous improvement of models in production.