Lilit Simonyan · Lead, Product Intelligence at ex-ServiceTitan Armenia
Assessed
Aug 26, 2026
Verification
Mid-Level Data Analyst Verification
Verdict: passed — Tatevik completed a practical mid-level Data Analyst assessment focused on understanding her current strengths and the areas that can help her progress toward her next career step.
2 partial
We discussed SQL, data quality, analytical thinking, and real-world business scenarios, with particular attention to communication, storytelling, and explaining insights to non-technical stakeholders. The session highlighted a solid analytical foundation and identified areas she can continue developing as she grows into stronger Data Analyst roles.
Tatevik has practical SQL experience and understands how to structure queries using core SQL concepts. The assessment showed that she would benefit from more practice with SQL nuances and from strengthening her critical thinking around how different query conditions affect the final result. Building a habit of carefully checking and validating query outputs will help her become more consistent and confident with SQL. Her broader background also includes data science and statistical modelling experience, which could be a strong asset in a Data Analyst role, although this was not a primary focus of this assessment.
Business Intelligence (BI)
Partial
Tatevik communicates insights clearly and has a good foundation in data storytelling. During the chart exercise, she was able to explain how she would interpret a sudden drop in repeat purchase rate and suggested going deeper by grouping the data across key categories to identify where the change was coming from. She also considered both internal and external factors, such as seasonality, marketing campaigns, and other events affecting the business or wider industry. Tatevik also has a nice portfolio demonstrating her experience with different BI and data visualization tools through practical projects. The main opportunity is to make this approach more consistent by always validating the data first, connecting the findings to the underlying product or business goal, and turning the analysis into a clear recommendation. Continued practice with different types of stakeholders and business scenarios will help her make her insights even more actionable and impactful.
Evidence
What happened in the session
Tatevik demonstrated good analytical thinking throughout the assessment. She was able to interpret what the data was showing, identify relevant trends, and suggest useful ways to investigate them, including looking at segments and other relevant dimensions. She also demonstrated awareness of common data-quality issues such as missing values, incorrect types, and invalid data, and understands how these can be addressed. In the chart exercise, she could clearly describe the main trend and suggest possible internal and external factors that might explain it. The main opportunity for further development is to go one layer deeper: ask more questions about what is driving the observed change, connect the analysis more closely to the underlying business or product goal, and challenge the data before drawing conclusions. Developing this deeper business curiosity and becoming more comfortable with ambiguous questions will help her move from explaining what the data shows to using it to uncover WHY it is happening and what the business should do next.
Action plan
What to do next
1
Practice end-to-end ownership: Take a real-life business scenario and work through the full process from A–Z: understand the core business problem, define the right questions and metrics, investigate the data, perform the analysis, and finish with a clear recommendation that addresses the original business goal. Pay attention to both the business context and the technical details along the way.
2
Develop an investigative mindset: When working with data, go beyond completing the requested task. Ask why data is missing, whether the numbers make sense, whether they are consistent with the real-world situation, and whether the results can be explained. Treat unexpected changes as something to investigate rather than simply report. Apply this mindset throughout the end-to-end exercise above.
3
Practice stakeholder-focused communication: For the same business scenario, practice explaining your findings to different stakeholders, focusing on what they need to know, why it matters, and what action you recommend rather than only presenting the analysis.
4
Use resources from https://www.datacamp.com/ for targeted practice: Use the available DataCamp resources to strengthen the areas identified in the assessment, particularly SQL, exploratory analysis, and data communication. Focus on practical exercises that require reasoning about the data and the business context, rather than only completing syntax-based tasks. DataCamp currently offers a broad variety of relevant courses.
