Support AI and analytics initiatives by performing exploratory data analysis (EDA), statistical analysis, and data wrangling.
Work closely with Data Scientists and AI Engineers to prepare high-quality datasets, uncover insights, validate assumptions, and improve data readiness for machine learning and advanced AI use cases.
Contribute to the development and deployment of modern machine learning, operational research, semantic analysis, and statistical methods for finding structure in large data sets.
Extract, join, and transform data from multiple sources using SQL and/or data tools.
Clean and preprocess structured and semi-structured data (handling missing values, duplicates, outliers, inconsistent formats).
Build and maintain analysis-ready datasets to support feature engineering and model development.
Perform EDA to understand data structure, relationships, distributions, and anomalies.
Identify trends, patterns, and data issues that may impact modeling performance or business interpretation.
Create clear visualizations and summaries to communicate key insights to technical and non-technical stakeholders.
Assist in measurement design, KPI definitions, and experimental analysis support (as needed).

Requirements

Bachelor’s degree (or equivalent practical experience) in a quantitative field such as Statistics, Mathematics, Economics, Computer Science, Data Science, Engineering, or similar with 0-3 years of working experience.
Familiarity with SQL for querying and manipulating data (joins, aggregations, filters).
Working knowledge of Python for data analysis (e.g., pandas/tidyverse, basic scripting).
Understanding of foundational statistics (distributions, summary stats, correlation, basic hypothesis testing concepts).
Ability to communicate clearly—especially when summarizing insights, assumptions, and data limitations.
Strong attention to detail and comfort working with messy or incomplete datasets.
Experience with data visualization tools (e.g., Tableau, Power BI) and/or Python visualization libraries.

Benefits

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

exploratory data analysisstatistical analysisdata wranglingSQLPythonpandasstatisticsdata visualizationfeature engineeringmachine learning

Soft Skills

communicationattention to detailproblem-solvingcollaborationanalytical thinking