• Design, build, and maintain Power BI dashboards and business reports for different departments. • Work closely with business users to understand reporting requirements and translate them into clear dashboards and analytics solutions. • Build reports related to trading activity, client performance, sales performance, revenue, deposits, withdrawals, account status, and operational KPIs. • Develop clean and scalable data models in Power BI using Power Query and DAX. • Ensure reports are accurate, consistent, and aligned with business definitions and KPIs. • Support Finance, Sales, Operations, Compliance, and Management teams with reporting and data analysis requirements. • Validate data quality and investigate issues related to mismatched numbers, missing data, or incorrect calculations. • Work with data engineering or database teams to understand data sources and improve reporting reliability. • Optimize Power BI reports for better performance, usability, and refresh efficiency. • Document report logic, KPIs, data sources, and business definitions. • Support ad hoc analysis and business requests when required.

Role Description The Data Analyst is responsible for the conception and creation of reports, data visualizations, and data summarization/analysis within BI software suites. This role executes the entire data analytics life cycle for their projects including: - Meeting with business stakeholders - Gathering requirements/discovery - Data preparation/cleaning - Building reports visualizations - Communicating results - Operationalization - Ongoing updates to existing products These projects span business stakeholders across the company (e.g. recruiting, financial, operations, clinical, IT, etc.). The Data Analyst works closely with the data BI team, end users, and developers. Qualifications - 2 years of experience in BI/reporting - 2 years of experience creating data visualizations in BI reporting suites (e.g. Qlik, PowerBI, Tableau, Domo, etc.) - 2 years of Advanced Excel experience - Basic understanding of SQL (i.e. basic functions: select, joins, group by, filtering, etc.) - Experience converting business requirements into actionable insights through data cleaning, interpretation, and interactive reporting/visualizations - Ability to work independently and make decisions in accordance with established policies and regulations - Ability to effectively work in fast-paced and complex environment, maintaining a sense of urgency - Will accept any suitable combination of education, training, and experience Requirements - Understanding of Python/R including pertinent data analysis libraries (e.g. for Python: jupyter notebook, sklearn, matplotlib, numpy, pandas, etc.; for R: Rstudio, tidyverse, caret, etc.) - Advanced knowledge of SQL (i.e. with clause, partition by, subqueries, etc.) - Knowledge of statistics and predictive modeling including, but not limited to linear regression – including the interpretation of residuals, logistic regression, unsupervised learning techniques, supervised learning techniques, ANOVA, and t-test, and the ability to interpret these outputs and present them to business stakeholders - Undergraduate degree in Mathematics, Computer Science, Statistics, Decision Science, or related field Benefits - $71,000 - $82,000 per year - Benefits (Start Day 1!): - Medical, Dental, Vision - Company Paid Life Insurance - Long-Term Disability and Short-Term Disability - Accident, Critical Illness - Legal Assistance, Identity Protection, Pet Coverage - Retirement Plan with Employer Match - Generous vacation plan + 8.5 paid holidays Core Values - Own Your Relationships – Be someone others can count on - Own the Outcome – Deliver results through accountability and follow-through - Obsess Over the Experience – Make every interaction meaningful - Act with Integrity & Respect – Do what’s right, always

• Projetar e implementar soluções de análise de dados • Trabalhar com equipes para coleta e organização de dados • Usar linguagens de programação para manipulação de dados • Colaborar em projetos de transformação digital

• Extract, review, and analyze data from spreadsheets, CSV files, reports, and legacy databases • Identify patterns, inconsistencies, and data quality issues across multiple files • Create data maps and transformation instructions based on required destination formats • Validate source data and recommend how it should be cleaned, structured, or interpreted • Test mapped and transformed data outputs for completeness and accuracy • Document findings, mapping logic, and process notes clearly for internal teams • Work closely with project managers and engineers to support successful data conversion projects • Help improve documentation, templates, and internal conversion processes