Data Analyst

Skandor Technologies · India

Company Description Skandor Technologies builds production-ready AI products that modernize enterprise workflows and strengthen data-driven decision-making. The company focuses on generative AI, automation, data platforms, and supply‑chain intelligence to help organizations unlock operational leverage. Skandor supports clients from product strategy and validation through deployment of scalable enterprise platforms. Team members work on real-world, high-impact use cases that shape how enterprises adopt AI and analytics.

Role Description This full-time remote Data Analyst role focuses on turning complex data into clear, actionable insights for internal teams and enterprise clients. The Data Analyst will collect, clean, and analyze large datasets, build dashboards and reports, and support data-driven decisions across AI, automation, and supply-chain projects. Typical tasks include defining metrics, performing statistical analyses, creating data models, and translating business questions into analytical approaches. The role also involves collaborating with product managers, engineers, and stakeholders to communicate findings, document methodologies, and recommend improvements to data quality and workflows.

Qualifications

• Candidates should possess strong Analytical Skills and proficiency in Data Analytics tools and techniques.
• Candidates should possess a solid foundation in Statistics for hypothesis testing, forecasting, and experiment analysis.
• Candidates should possess experience in Data Modeling, including structuring data for reporting and building scalable analytical datasets.
• Candidates should possess clear and effective Communication skills to explain complex findings to technical and non-technical stakeholders.
• Proficiency with SQL and at least one analytics or scripting language (e.g., Python, R) is highly beneficial.
• Experience with business intelligence or visualization tools is preferred.
• Familiarity with cloud data platforms (e.g., AWS, GCP, Azure) and modern data stacks is an advantage.
• Bachelor’s degree in a quantitative field such as Data Science, Statistics, Mathematics, Computer Science, Engineering, or a related discipline, or equivalent practical experience.