Job Summary

This is a unique opportunity to gain broad experience, have significant responsibility for a variety of projects and engage with key decision makers. The Data Analytics Analyst is responsible for independently designing data modeling processes (build complex data models from scratch) that support strategic and operational priorities and drive data-driven decisions, creating algorithms and predictive models to extract the data the business needs, and helping analyze the data and share insights with peers. The role will also assume the responsibility of researching best practices in the industry and gathering competitive intelligence to identify potential trends and risks in the market.

• Design, develop, and deploy Generative AI solutions using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, and prompt engineering techniques.
• Build production-ready APIs and AI services to integrate machine learning models into enterprise applications and business workflows.
• Perform quantitative research in the business-related field and other thematic areas. Research includes data mining, model building/maintenance, and developing reports to answer data-related queries
• Generate and test hypotheses using appropriate econometric study designs and extract meaningful evidence-based narratives from technical analyses
• Produce and analyze comparative statistical reports to identify trends, patterns, or fluctuations in key performance indicators (KPIs), and recommends key ideas to senior management
• Develop, train, and evaluate Machine Learning models (regression, classification, clustering, time series, etc.) This includes data cleaning, selecting appropriate algorithms/ feature engineering, exploratory data analysis, training models, and evaluating their performance.
• Assist in building end-to-end data science pipelines from data ingestion to model deployment
• Assess the performance of the models using metrics such as accuracy, precision, recall, F1-score and model tuning to improve performance.
• Willingness to learn and adapt to new tools, technologies, and techniques in the rapidly evolving field of data science.
• Locate and define new process improvement opportunities

• 3+ years of work experience in applying various statistical and machine learning methods, such as regression, classification, forecasting and causal inference is required
• Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, Statistics, Mathematics, Engineering, or another quantitative discipline.
• Solid grasp of microeconomic/consumer theory, experimental design, and sensitivity analysis
• Strong technical skills: Programming tools (i.e., R, Python); Cloud Software (Azure ML, Microsoft Fabric, Google Analytics, Snowflake); data visualization tools (i.e., Tableau, Power BI, Qlik Sense); data querying tools (i.e., SQL, Business Objects)
• Familiarity with creating and deploying Gen-AI Agents and ML Applications
• Familiarity with data science libraries and tools such as scikit-learn, TensorFlow, or PyTorch/ PySpark for machine learning, and Jupyter Notebook or RStudio for data analysis
• Establishes and maintains effective relationships with internal business stakeholders by fully understanding and meeting their expectations
• Ability to work in a rapidly evolving environment, while quickly grasping and applying new concepts in order to meet deadlines under pressure with accurate and relevant analysis
• Excellent written and verbal communication skills with a high degree of accuracy and attention to detail
• This position requires minimal travel on an as-needed basis
• There are minimal physical requirements for this position

Student Loan Repayment Assistance Program

Benjamin Moore provides Student Loan Repayment Assistance Program to support eligible active employees who graduated from an accredited post-secondary educational institution. The Repayment Program is intended to contribute to reducing employee's student loans. The Company follows all rules and regulations concerning the taxability of student loan repayments provided under applicable law.