Data Analyst

What can a Remote specialist of the Myspecialist network do for your application for "Data Analyst"?

Figures that differ depending on the tool consulted, Excel reports rebuilt by hand every month, KPIs nobody knows how to recalculate, decisions made without visibility on margins or trends: in many companies, the data exists but cannot be used. Making it useful requires understanding the business questions, making sources reliable, building consistent indicators and presenting results in a form decision-makers can read.

Here is what a Data Analyst from MySpecialist can take on:

• Requirements gathering and scoping: identifying business questions, the decisions to support and the indicators that matter for management, sales, marketing, finance or operations.
• Data collection and consolidation: extracting data from the ERP, CRM, accounting software, e-commerce platform, Google Analytics or internal files, and combining sources into a consistent model.
• Data cleaning and validation: detecting duplicates, missing values, inconsistencies and input errors, and documenting the correction rules applied.
• KPI definition: formalising indicators, how they are calculated, their scope and update frequency so that everyone reads the same figures.
• Queries and data modelling: writing SQL queries, preparing datasets and building data models suited to reporting and analysis.
• Dashboards: designing dashboards in Power BI, Looker Studio, Tableau or Metabase, with filters, drill-downs and visualisations tailored to each audience.
• Ad hoc analysis: profitability by product, customer or channel, sales, churn, inventory or campaign effectiveness analysis, with actionable conclusions.
• Variance and anomaly analysis: identifying unusual fluctuations, comparing budget and actuals, and investigating the causes behind observed trends.
• Reporting automation: replacing manual spreadsheets with automatically refreshed reports using advanced Excel, Power Query, Python or available connectors.
• Presentation and synthesis: presenting findings as notes, charts and recommendations that non-technical stakeholders can understand.
• Documentation and maintenance: documenting sources, calculations and reports, monitoring that they run correctly and adapting them as tools or needs change.

The Data Analyst can set up a first reliable reporting layer in an SME still running on spreadsheets, or strengthen an existing data team on recurring analysis, a visualisation tool migration or a KPI structuring project.