SSE- Data Analyst(IIT/NIT)

Company Overview

BOLD is revolutionising the career landscape by empowering individuals to discover and develop their professional paths. Our recent acquisitions of Monster and CareerBuilder will expand our global reach and impact. With a range of brands like FlexJobs, Zety, and Sonara and more, we provide job seekers with the tools to create impressive resumes and connect with employers. BOLD fosters a dynamic, inclusive culture that prioritises innovation and growth. So don't wait and join us in shaping the future of work and redefining successful careers.

Position Overview:

Were looking for a Data Analyst who enjoys getting to the heart of a business question. Youll work with large datasets, define reliable metrics, and turn your findings into recommendations that product and business teams can use.

The work goes beyond building reports. Youll investigate changes in customer behaviour and business performance, test ideas, and help teams decide what to do next. Youll have room to take ownership of problems from the first question through to a clear answer.

Required Skills :

• Strong SQL skills, including experience working with complex queries and large datasets.
• Working proficiency in Python or R for data analysis.
• A sound foundation in mathematics and statistics, with the ability to choose and apply appropriate methods to real problems.
• Experience with descriptive analytics and a working understanding of machine learning concepts and their practical use.
• Strong problem-solving and analytical thinking: you can break down an ambiguous question, test assumptions, and follow the evidence.
• The ability to explain findings clearly to both technical and non-technical colleagues.
• Curiosity about how products and businesses work, along with the ownership to follow an analysis through to a useful outcome.

Responsibilities

• Analyse business and product performance to identify trends, risks, and opportunities.
• Use SQL to extract, combine, and analyse large volumes of data from multiple sources.
• Python or R to explore data, test hypotheses, and solve open-ended problems.
• Build and improve metrics, reporting and simulations that teams can rely on.
• Analyse website journeys, event data, and customer behaviour to understand where users engage or drop off.
• Apply statistical methods to evaluate changes and experiments, and explain the strength and limits of your findings.
• Use descriptive analytics, segmentation and where useful, machine learning methods to answer business questions.
• Work with product, marketing, engineering, and business teams to frame questions and turn analysis into actionable recommendations.