Team Lead (Manager) - Focused on climate analytics

Key Skills

Data science techniques, Effective communication skills, Leadership Skill, Python Programming, Teamwork, Writing

Job Description

The role and responsibilities

We are looking for a highly talented quantitative Team Lead/Director to continue the success and development of our climate analytics for wholesale exposures.

The ideal candidates will possess strong technical skills, capability to lead and manage teams, deliver projects efficiently and under high quality standards and have an open and flexible mindset.

We offer a clear career path to partner level, with potentially steeper trajectory than in similar firms.

This position offers excellent career and growth opportunities and a wide set of responsibilities from the start:

• You will oversee the development of our wholesale climate analytics, in collaboration with a prestigious partner and both from a technical and commercial perspectives

Work will include:

• Roadmap development
• Methodology development (transition and physical risk)
• Developing hypotheses; managing data collection, model creation and analyses; conducting primary and secondary research; creatively tackling information limitations; and surfacing insights, overseeing the work of analysts
• Methodology implementation
• Participating in and leading client pitches
• Collecting feedback from clients
• Interacting with modeling partners
• Using Partners and the internal network effectively to provide technical and senior-level steer to projects
• Working in a team to complete project deliverables to high standard
• Maintaining energy and positive work life balance of the team
• Coaching, guiding and managing Oliver Wyman and client team members to develop their skills

Working with us offers excellent career and growth opportunities for highly motivated professionals with relevant prior experience in data analytics, including data engineering, model development and/or model validation. Experience in applying analytics to applications in the financial services industry, such as in credit risk, market risk, pricing, forecasting and stress testing will be particularly relevant.

Your attributes and experience

Clients hire Oliver Wyman for specialized expertise and the impact we deliver. The ideal candidate will have most of the following:

• Bachelor’s, Master’s or PhD degree in a quantitative discipline. Ideally Mathematics, Statistics, Data Science, Economics, Physics, Computer Science, Sustainability, or Engineering
• Minimum 3-4 years work experience in a data analytics role with management and leadership experience, ideally related to the Financial Services industry
• Strong quantitative analysis skills
• Strong communication skills and ability to effectively present results, potential issues and implications
• Excellent financial analysis skills
• Work effectively and collaboratively in a team while coaching and guiding junior team members and contributing to their development
• Be independent and work under limited supervision respecting defined timelines
• Ability to manage time and work processes efficiently to meet deadlines in a fast-paced environment
• Be able to find innovative, practical and flexible solutions to business issues
• Excellent command of English language (verbal and written)
• Background/interest in climate change/sustainability related topics
• Ability to maintain and respect confidentiality

The ideal candidate will also have some of the following skills and qualifications:

• Experience in developing solutions for quantitative analyses using advanced analytics and data manipulation software in Python
• Previous experience financial services analytics (through course work, internships, etc.) with content in one or more of the following areas: credit risk measurement (e.g. Probability of Default, Loss Given Default, Exposure at Default), stress testing, financial modelling, RWA calculations, credit portfolio

The applicable base salary range for this role is $150K - $200K.

The base pay offered will be determined on factors such as experience, skills, training, location, certifications, and education. Decisions will be determined on a case-by-case basis.