AI Analyst

Company Description

Adroitent is a global leader in leveraging AI, Automation, and Analytics to deliver transformative technology solutions for enterprises and startups alike. Headquartered in Princeton, NJ, with a strong presence across multiple regions including the Middle East, Europe, and Asia, Adroitent provides innovative cloud-enabled solutions for modern business challenges. With over a decade of expertise and 5000 person-years of agile delivery experience, the company specializes in reducing time to market, driving efficiency, and enabling digital transformations. By combining cutting-edge technologies with an agile delivery framework, Adroitent empowers businesses to thrive in the fast-evolving digital landscape.

AI Requirements Gathering & Analysis

Partner with business stakeholders across merchandising, supply chain, marketing, store operations, and e-commerce to identify AI opportunities and gather detailed requirements

Conduct workshops, interviews, and collaborative sessions to understand business pain points, processes, and objectives that can be addressed through AI

Translate complex business needs into clear, actionable AI/ML requirements and user stories for data scientists, AI-ML engineers

Define success metrics, acceptance criteria, and KPIs for AI projects to ensure alignment with business goals

Create detailed business requirement documents (BRDs), functional specifications, and process flow diagrams

Prioritize AI use cases based on business impact, feasibility, and strategic alignment

Serve as the liaison between business users and technical teams, ensuring clear communication and mutual understanding.

Data Analysis & Insights

Perform exploratory data analysis (EDA) to understand data patterns, identify anomalies, and assess data quality for AI model development

Analyze large datasets from multiple sources including POS systems, e-commerce platforms, inventory systems, and customer databases

Create data visualizations and dashboards to communicate insights to stakeholders and support data-driven decision-making

Conduct statistical analysis to validate hypotheses and identify trends that inform AI model design

Profile and assess data sources to determine their suitability for AI/ML applications

Identify data gaps, quality issues, and opportunities for data enrichment to improve model performance

Work with data engineers to define data requirements and ensure proper data collection and storage

Generate regular reports on AI system performance, business impact, and ROI metrics

AI Testing & Quality Assurance

Design and execute comprehensive test plans for AI/ML models including functional, integration, performance, and user acceptance testing (UAT)

Validate AI model outputs against business requirements and acceptance criteria to ensure accuracy and reliability

Perform model performance testing using appropriate metrics (accuracy, precision, recall, F1 score, AUC-ROC, RMSE, etc.)

Conduct bias detection and fairness testing to ensure AI models dont discriminate or produce unintended outcomes

Test AI systems across different scenarios, edge cases, and data distributions to identify potential failures

Document test cases, test results, and defects in a clear, organized manner using Jira.

Work closely with data scientists and AI/ML engineers to reproduce, troubleshoot, and resolve model issues

Validate data quality, feature engineering, and model training processes to ensure robust AI solutions

Conduct A/B testing and champion/challenger tests to compare model performance and validate improvements

Monitor deployed AI models for drift, degradation, and anomalies, raising alerts when performance deviates from expectations

Required Qualifications

Bachelors degree in Business Analytics, Data Science, Computer Science, Information Systems, Statistics, or related field

5+ years of experience as a Business Analyst, Data Analyst, QA Analyst, or similar role, preferably with exposure to AI/ML projects

Preferred Retail experience.

Strong analytical skills with experience in data analysis, statistical analysis, and data visualization

Proficiency in SQL for querying and analyzing data from multiple data sources. Preferable experience with Databricks.

Experience with data visualization tools (Tableau, Power BI, Looker, or similar)

Hands-on experience with Python or R for data analysis and scripting

Knowledge of AI/ML fundamentals including supervised/unsupervised learning, classification, regression, and model evaluation metrics

Experience with testing methodologies and creating test plans, test cases, and test scripts

• Proficiency with collaboration and documentation tools (Confluence, Jira, Microsoft Office, Google Workspace)