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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Analyst - **Company:** Credx LLC - **Location:** New York, NY, United States - **Experience:** Experienced - **Salary:** $84,926.0 - $93,346.0 - **Contract:** Permanent contract - **Skills:** Microsoft Excel, A/B Testing, Agile Methodology, Airflow, Amazon Web Services, Data Analysis, Microsoft Azure, Big Data, Software as a Service, Profiling, Information Systems, Data Cleansing, Information Engineering, Data Governance, Data Integration, Extract Transform Load (ETL), Data Transformation, Data Visualization, Data Warehousing, Relational Databases, Excel Formulas, Executive Information Systems, Statistical Hypothesis Testing, Python (Programming Language), Machine Learning, Meta-Data Management, NumPy, Pivot Tables, Query Optimization, Power BI, Cloud Services, SQL Databases, Systems Integration, Tableau (Software), Workflow Management Systems, Privacy Controls, Jupyter Notebook, Google Cloud, Enterprise Software Applications, Snowflake, Model Validation, Git, Powerquery, Pandas, Information Technology, Data Analytics, Google Bigquery, Api Design, Azure Synapse Analytics, Looker Analytics, Software Version Control, Data Pipelines, Amazon Redshift, Databricks - **Published:** August 2, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=33d1d1e08a556796 ## About the Role * Bachelor's or Master's degree in Data Analytics, Computer Science, Information Systems, Statistics, Mathematics, Business Analytics, Economics, Engineering, or a related quantitative field. * 3-5 years of professional experience as a data analyst or in a similar analytical role. * Advanced proficiency in SQL, including joins, window functions, common table expressions (CTEs), aggregations, and query optimization. * Strong experience with Microsoft Excel, including advanced formulas, PivotTables, Power Query, and data analysis techniques. * Hands-on experience with business intelligence and data visualization tools such as Tableau, Power BI, Looker, or similar platforms. * Experience analyzing large datasets and transforming raw data into actionable business insights. * Strong understanding of data modeling, relational databases, and data warehousing concepts. * Experience writing complex analytical queries and developing automated reporting solutions. * Proficiency in Python or R for data analysis, automation, and statistical analysis. * Experience with data cleaning, validation, profiling, and quality assurance. * Strong understanding of descriptive statistics, hypothesis testing, trend analysis, and business performance measurement. * Ability to interpret business requirements and translate them into analytical solutions. * Experience creating executive dashboards, scorecards, and KPI reporting. * Strong analytical thinking and problem-solving abilities. * Excellent communication and presentation skills with the ability to explain technical findings to non-technical audiences. * Experience working in Agile or cross-functional business environments. * Ability to manage multiple priorities while meeting project deadlines., * Master's degree in business analytics, data science, statistics, computer science, or a related discipline. * Experience with cloud data platforms such as Snowflake, Google BigQuery, Amazon Redshift, Azure Synapse Analytics, or Databricks. * Experience working with ETL/ELT processes and data integration tools. * Familiarity with dbt, Apache Airflow, or similar data transformation and orchestration tools. * Experience using cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform. * Knowledge of statistical modeling, predictive analytics, and forecasting techniques. * Experience supporting A/B testing, experimentation frameworks, and causal analysis. * Familiarity with data governance, metadata management, and data quality frameworks. * Experience working with APIs and integrating external data sources. * Knowledge of version control systems such as Git. * Experience with scripting and automation using Python, Pandas, NumPy, or Jupyter Notebooks. * Familiarity with machine learning concepts and model evaluation techniques. * Experience working in SaaS, fintech, healthcare, e-commerce, enterprise software, or high-growth technology organizations. * Professional certifications in Tableau, Microsoft Power BI, Microsoft Azure Data, AWS Analytics, Google Cloud Data Analytics, or equivalent certifications. * Demonstrated ability to influence business decisions through data-driven recommendations. ## Description * Collect, clean, validate, and analyze large datasets from multiple internal and external data sources. * Develop and maintain dashboards, reports, and visualizations to support business operations and strategic decision-making. * Analyze business performance, customer behavior, operational metrics, and product performance to identify trends, opportunities, and risks. * Partner with business stakeholders, product managers, engineering teams, finance, marketing, and operations to translate business questions into data-driven insights. * Design and execute ad hoc analyses to support business initiatives and executive decision-making. * Create recurring reports and automate reporting processes to improve operational efficiency. * Develop SQL queries to extract, transform, and analyze structured data from relational databases. * Validate data accuracy, identify anomalies, and ensure consistency across reporting systems. * Define, monitor, and maintain key performance indicators (KPIs) and business metrics. * Build interactive dashboards using business intelligence tools to communicate insights effectively. * Perform exploratory data analysis to identify patterns, correlations, and business opportunities. * Support A/B testing, experimentation, and performance measurement initiatives. * Collaborate with data engineering teams to improve data pipelines, data models, and reporting infrastructure. * Document business definitions, reporting logic, metric calculations, and analytical methodologies. * Present findings and recommendations to technical and non-technical stakeholders through clear visualizations and presentations. * Identify opportunities to improve business processes using data and analytics. * Ensure compliance with organizational data governance, security, and privacy standards. * Stay current with emerging analytics tools, technologies, and industry best practices. ## 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