Associate Data Analyst

Associate Data Analyst

Job Category

Data & Analytics

Requisition Number

ASSOC006954

Posting Details

Posted

July 31, 2026

Full-Time

Remote

LocationsShowing 1 location

Remote / Virtual

Job Details

Description

The Associate Data Analyst position performs data analytics for informed decision making, dashboards, report generation and overall project support. This role supports and contributes to organizational success by supporting the delivery of high-quality data solutions. Work is performed under general supervision with guidance provided for complex issues.

Responsibilities

Proactively gather data from diverse internal systems (e.g., CRM platforms, ERP systems, operational databases) and external sources (e.g., public datasets, APIs, third-party vendors, customer surveys).

Apply robust data cleaning techniques such as handling missing values, correcting data types, removing duplicates, and standardizing formats to ensure high data quality.

Validate data accuracy by cross-referencing with source systems, applying logic checks, and collaborating with domain experts to confirm assumptions.

Organize raw data into structured formats—such as data tables, CSV files, or relational databases—making it accessible and ready for analysis by analysts, data scientists, and business stakeholders.

Conduct exploratory data analysis using statistical techniques (e.g., regression, clustering, hypothesis testing) to uncover hidden patterns, anomalies, and relationships within datasets.

Visualize trends over time, segment customer behavior, and identify key performance drivers using tools like matplotlib, seaborn, or built-in Excel charts.

Translate analytical findings into actionable insights that support strategic initiatives such as market expansion, product optimization, or customer retention.

Respond to data-related inquiries from business units by investigating root causes, validating assumptions, and delivering clear, data-backed answers.

Design and build dynamic dashboards that track KPIs, operational metrics, and business performance using visualization tools like Tableau, Power BI, or Excel.

Write efficient SQL queries to extract, join, filter, and aggregate data from relational databases such as MySQL, PostgreSQL, or Microsoft SQL Server.

Leverage programming languages like Python or R to automate data workflows, perform advanced statistical analysis, and build custom data pipelines.

Collaborate with cross-functional teams—including marketing, product, finance, and operations—to understand their goals and translate them into data requirements.

Maintain detailed documentation of data sources, definitions, transformation logic, and business rules to ensure transparency and consistency across reports.

Monitor data integrity by setting up validation checks, reconciling discrepancies, and working with IT or engineering teams to resolve issues.

Help standardize procedures for data handling, reporting, and analysis by creating templates, SOPs, and training materials for team members.

Flexibility to adapt and execute various additional assignments based on evolving needs.

Mentorship

May provide mentorship, guidance, support, and knowledge-sharing to help less experienced team members develop their skills and grow within their roles.

Skills and Competencies

Proficiency in SQL for data extraction, transformation, and analysis

Advanced Excel and Google Sheets skills, including pivot tables and complex formulas

Experience with data visualization tools such as Tableau, Power BI, or Excel dashboards

Strong analytical skills with knowledge of statistical methods (e.g., regression, clustering)

Ability to perform exploratory data analysis and identify actionable insights

Familiarity with Python or R for data manipulation and visualization (preferred)

Skilled in cleaning, validating, and transforming large datasets

Excellent communication skills for presenting data to non-technical stakeholders

Collaborative mindset with experience working across departments

Detail-oriented with a focus on data accuracy and consistency

Knowledge of data governance, metadata management, and quality assurance practices

Understanding of data privacy and compliance standards (e.g., GDPR, CCPA)

Ability to identify process inefficiencies and recommend improvements

Experience supporting senior analysts with modeling, forecasting, and reporting

Experience

Typically, a minimum of 2 years’ related work experience in Data Analytics or a related field is required.

Education

A bachelor's degree in a quantitative field (e.g., Mathematics, Statistics, Economics, Computer Science, or related discipline) is required.