Data Analyst

Company Description SimuLab is an innovative AI-native platform revolutionizing management education by replacing outdated case studies with dynamic, experiential learning through realistic business simulations. Driven by Agentic AI and no-code workflows, SimuLab immerses MBA students in real-time scenarios like supply chain crises and CRM automation. Based on fast-moving startup environments, these simulations prepare students for the complexities of modern business challenges.

For educators, our platform offers a creator engine for seamless deployment of customized scenarios, fostering the development of agile, industry-ready leaders. Role Description This is a full-time on-site role for a Data Analyst based in Bengaluru. The Data Analyst will be responsible for collecting, processing, and analyzing data to generate business insights.

The role involves creating data models, conducting statistical analysis, and delivering actionable insights through clear, effective communication. Collaborating with cross-functional teams, the Data Analyst will help inform strategic decisions and improve the overall efficiency of SimuLab’s product offerings. Key Responsibilities Data Management: Extract, clean, and structure large datasets from multiple sources using SQL and Python to ensure they are ready for analysis and AI modeling.

AI & Machine Learning Support: Assist data scientists and engineers in preparing training data, running basic predictive models (e.g., regressions, clustering), and evaluating model performance. GenAI Integration: Utilize Large Language Models (LLMs) and prompt engineering to automate routine data extraction, summarize qualitative data (like customer feedback), or streamline reporting. Dashboarding & Reporting: Build, maintain, and optimize interactive dashboards using (Power BI / Tableau / Metabase) to track Key Performance Indicators (KPIs).

Business Insights: Analyze data to identify anomalies, trends, and opportunities. Translate these technical findings into simple, actionable presentations for non-technical stakeholders. Required Qualifications Education: Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Mathematics, Economics, or a related quantitative field.

Programming: Strong proficiency in Python (specifically Pandas, NumPy, and Matplotlib/Seaborn) and SQL for database querying. AI/ML Fundamentals: A solid conceptual understanding of basic machine learning algorithms and the data lifecycle. Problem-Solving: Exceptional critical thinking skills with the ability to look at a business problem and determine the right data needed to solve it.

Communication: Strong \"data storytelling\" skills. You must be able to explain the “why” behind the numbers to management and business teams. Preferred Skills (Bonus Points) Portfolio: A GitHub or Kaggle portfolio showcasing 2-3 end-to-end data projects (especially those involving predictive modeling or AI APIs).

Tools: Experience with GenAI APIs (OpenAI, Gemini) or automation workflows. Cloud Basics: Familiarity with cloud data environments (e.g., AWS, Google Cloud Platform, or Snowflake). Spreadsheets: Advanced Excel/Google Sheets skills (Pivot Tables, complex functions).

What We Offer Mentorship & Growth: Direct collaboration with senior engineers/analysts to accelerate your technical skills. Impact: The opportunity to work on real-world AI applications that directly impact business revenue and strategy. Compensation: Competitive entry-level salary