WFM Forecaster working student

Location: Saint-Ouen, 93, FR

WFM Forecaster working student

Job Level

Student

Location

Saint-Ouen, 93, FR, 93400

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Area of Expertise

Operations

Unit

Allianz Partners

Employing Entity

AP Solutions GmbH Branch in France

Job Type

Part-Time

Remote Job

Hybrid working

Employment Type

Temporary

ID

109139

Position Cluster

n.a.

This role sits in Global Operations (COO), in the Workforce Management team. Our job is to make sure we have the right people in the right place at the right time so that global operations run smoothly and we meet our service levels.

We’re looking for a Working Student / Intern who enjoys working with data and code, and wants hands-on experience with time series forecasting in a real global business. If you like Python, statistics, building (and improving) forecasts, and turning analysis into clear reports and dashboards for decision-makers, this is likely a good fit.

What you do

You will spend your time

Supporting forecast managers in developing and improving forecast models for operations volumes and staffing needs (FTEs and productivity) across different business units.

Building and automating reports and dashboards (e.g. in notebooks) to monitor forecast accuracy and key Workforce Management metrics.

Gathering and structuring data for management requests, and turning it into clear presentations and materials for senior leadership.

Assisting with project management tasks: organizing meetings, preparing materials, tracking progress and supporting communication across teams.

Contributing to regular reporting cycles and updates between global, regional, and local teams, helping ensure information flows smoothly.

Collaborating with other departments on ad hoc analyses and strategic initiatives related to operations and Workforce Management.

Work effectively in an environment shaped by artificial intelligence (AI), machine learning, data analytics and cloud-based tools, using insight responsibly and in line with our standards for data governance, security and ethical use

What you bring

Strong computational and programming skills: you are comfortable working with data in code, not just in spreadsheets, and can structure your work clearly so others can use it.

Knowledge of statistics and time series analysis: you understand core concepts (e.g. trends, seasonality, error metrics) and can apply them in simple forecasting tasks.

Experience with Python, notebooks and git/github: you can write and run analysis scripts, version your work and collaborate using modern data workflows.

Genuine interest in time series forecasting and operations topics: you want to learn how forecasting is used to steer a global service operation and are willing to dive into real business data.

Intermediate level of English: you can read and write documentation, and communicate your findings in calls and meetings with international colleagues.

How we hire

We hire directly. Allianz Partners does not accept unsolicited CVs or approaches from agencies. We only work with partners on our approved supplier list, under contract. Any unsolicited submissions will not be considered.

109139 | Operations | Student | n.a. | Allianz Partners | Part-Time | Temporary

Allianz Group is one of the most trusted insurance and asset management companies in the world. Caring for our employees, their ambitions, dreams and challenges, is what makes us a unique employer. Together we can build an environment where everyone feels empowered and has the confidence to explore, to grow and to shape a better future for our customers and the world around us.

At Allianz, we stand for unity: we believe that a united world is a more prosperous world, and we are dedicated to consistently advocating for equal opportunities for all. And the foundation for this is our inclusive workplace, where people and performance both matter, and nurtures a culture grounded in integrity, fairness, inclusion and trust.

We therefore welcome applications regardless of ethnicity or cultural background, age, gender, nationality, religion, social class, disability or sexual orientation, or any other characteristics protected under applicable local laws and regulations.

Great to have you on board. Let's care for tomorrow.