Data Analyst

Company: Wynisco Website: Visit Website LinkedIn: Visit LinkedIn Business Type: Startup Company Type: Product Business Model: B2B Funding Stage: Pre-seed Industry: Information Technology Job Description We're looking for a Data Analyst to collect, process, and analyze data, build reliable data pipelines, and uncover actionable insights that support data-driven decision-making across the organization. Key Responsibilities • Gather data from multiple sources (databases, APIs, spreadsheets) and ensure its accuracy, consistency, and completeness. • Clean, transform, and prepare raw data for analysis using Python and SQL. • Build and maintain data pipelines (ETL/ELT) to automate data collection, transformation, and loading. • Perform exploratory and statistical analysis to identify trends, patterns, and correlations. • Build, automate, and maintain dashboards and reports using BI tools (Power BI, Tableau, or Looker Studio). • Write and optimize SQL queries to extract and manipulate data. • Apply AI/ML techniques where relevant — predictive analysis, segmentation, forecasting and leverage AI tools to improve analysis and reporting efficiency. • Translate business questions into analytical problems and communicate findings clearly to stakeholders. • Define, track, and report on KPIs; flag anomalies and opportunities proactively. • Document data definitions, methodologies, and pipeline/reporting processes; maintain data quality standards. Requirements • Bachelor's degree in Statistics, Mathematics, Computer Science, Economics, or a related field • 2–5 years of experience in data analysis • Strong proficiency in Python (pandas, NumPy) and SQL • Experience building or maintaining data pipelines (ETL/ELT); exposure to tools like • Airflow, dbt, or cloud data services a plus • Hands-on experience with at least one BI/visualization tool (Power BI, Tableau, Looker Studio) • Basic knowledge of AI/ML concepts (regression, classification, forecasting) and • familiarity with AI tools (e.g., ChatGPT/LLM-based workflows) for productivity • Solid understanding of descriptive statistics; A/B testing knowledge a plus • Strong analytical thinking, attention to detail, and communication skills