Your mission
Our Market Intelligence and Business Development team plays a pivotal role in driving our company's strategic growth within the fast-evolving eMobility sector. We focus on harnessing the power of data to inform our decision-making processes and guide our expansion. As part of our team, you'll develop sophisticated data models, enhance our internal databases, and deliver actionable insights that fuel our business strategies.Join us as a Working Student - Market Intelligence & Business Development (f/m/x) and contribute to shaping the future of sustainable mobility through data-driven innovation.
Key Responsibilities
Data Collection & Analysis: Gather, synthesize, and analyze data from a variety of sources, transforming raw data into meaningful insights that directly support strategic decision-making and business development initiatives.
Dashboard Development: Define data requirements and create dynamic, visually compelling dashboards using MS PowerBI, ensuring that insights are easily accessible and actionable for key stakeholders.
Collaboration & Reporting: Work closely with cross-functional teams and report directly to the Head of Business Development & Market Intelligence, providing regular updates on data-driven insights and recommendations.
Machine Learning & AI Enablement: Support the development and implementation of advanced analytics and machine learning solutions to uncover predictive insights. Leverage predictive modeling and AI-driven approaches to generate deeper market and business insights.
Your profile
Analytical Mindset: Strong passion for unraveling complex business questions through data-driven insights. Ability to translate analytical findings into strategic business actions.Technical Expertise: Deep understanding of data processing, analytics, and business insight generation. Proficient in Python and SQL for data manipulation and analysis.
Dashboard & Visualization Skills: Hands-on experience with MS PowerBI for creating interactive dashboards that aid in executive decision-making.
Machine Learning Experience (Preferred): Initial hands-on experience or academic exposure to advanced analytics and machine learning techniques, including predictive modeling, statistical analysis, or AI-driven data applications, is considered a plus.
Industry Affinity: Genuine interest in eMobility and a desire to contribute to the growth and innovation within the EV charging industry.