Forecast Analyst

As a Forecast Analyst at SolarEdge, your primary responsibilities will include analyzing historical sales data, developing forecasting models, collaborating with cross-functional teams, and preparing detailed reports on forecast performance. You will play a key role in supporting strategic planning with your findings and insights, ensuring that our decisions are backed by accurate and actionable data.

To qualify for the Forecast Analyst position at SolarEdge, candidates typically need a Bachelor's degree in Statistics, Economics, Business, Data Science, or a related field, along with 3-5 years of experience in a similar analytical role. Proficiency in statistical software and advanced Excel skills are essential, as well as strong analytical and problem-solving abilities.

A Forecast Analyst at SolarEdge should be proficient in statistical software such as R, SAS, or SPSS, and possess advanced Excel skills. Familiarity with data visualization tools like Tableau or Power BI is also valuable. Furthermore, knowledge of SQL and machine learning algorithms will enhance your ability to analyze data and develop forecasting models.

At SolarEdge, we are committed to the professional growth of our employees. As a Forecast Analyst, you will receive training on forecasting tools and techniques, and you will have opportunities to work closely with experienced professionals from various departments. Our culture promotes continuous learning and development, providing you with the resources necessary to advance in your career.

The workplace culture for Forecast Analysts at SolarEdge is collaborative and inclusive. We value diverse perspectives and foster a work environment where every team member feels empowered to contribute ideas and insights. You will have the opportunity to work with dynamic teams and participate in initiatives that aim to create innovative solutions for a sustainable future.

In creating a forecasting model, I start by gathering historical data and identifying relevant variables that could impact future outcomes. I then analyze the data for patterns and trends, applying various statistical methods to develop the model. It’s important to validate the model's accuracy by comparing its predictions with actual results and making adjustments as necessary.

I am proficient in statistical software such as R and SPSS. In my previous role, I utilized these tools to analyze sales data and develop predictive models that helped identify market trends, which directly influenced strategic decisions and improved forecast accuracy.

In a previous project, my forecast underestimated demand due to an unexpected market trend. This experience taught me the importance of incorporating scenario analysis and being adaptive to changing conditions. I learned to enhance my model with real-time data and to remain flexible in my approach, ensuring ongoing communication with stakeholders.

Monitoring forecast accuracy involves regularly comparing predicted outcomes with actual results and analyzing discrepancies. I use statistical metrics such as Mean Absolute Percentage Error (MAPE) to quantify accuracy and identify areas for improvement, adjusting models as necessary to incorporate new data and insights.

I make it a priority to establish clear communication channels with cross-functional teams. I collaborate closely with sales, marketing, and finance to understand their perspectives and gather data. Regular meetings and updates ensure that everyone is aligned and that the information used for forecasting is comprehensive and accurate.

I have experience using Tableau and Power BI to create visual representations of data. These tools help in identifying patterns and trends quickly, enabling me to present complex data in an easily digestible format to stakeholders, which is vital for strategic discussions and decision-making.

To ensure data integrity, I prioritize thorough data cleaning and validation processes. I cross-check data sources for accuracy and completeness, and I maintain meticulous documentation of data origins and processing steps, which helps in building trust in the forecasts I present.

I regularly stay informed about industry trends and economic indicators that could affect forecasts. I analyze how these external factors correlate with historical data, incorporating them into my models to enhance accuracy. Scenario analysis helps me to assess potential impacts and prepare for various outcomes.

I have had experience with demand planning, where I collaborated with supply chain teams to align forecasts with inventory levels. By analyzing sales trends and seasonality, I helped ensure that stock levels were optimized, reducing excess inventory and minimizing shortages.

I am drawn to the Forecast Analyst role at SolarEdge because I am passionate about renewable energy and sustainability. I admire SolarEdge’s commitment to innovation and clean energy solutions and believe that my analytical skills can contribute to advancements in this field, making a positive impact on the environment.