Data Science & Analytics Intern (Hybrid)

DURATION: 1/1/2025-5/31/2025

At Benjamin Moore, we empower our team members to achieve their goals and make a positive impact in our communities. We offer a rewarding and inspiring work environment that fosters creativity, collaboration, and a strong sense of camaraderie. Our culture of excellence and transparency encourages our colleagues to bring their authentic selves and unique perspectives/ideas every day. With 140 years of rich history behind our brand, we know that our people are the driving force behind our success. We believe in investing in our colleagues by offering work-life balance, competitive/ benefits, ongoing learning/continuing education, and skill development. Through a positive and engaging workplace, we facilitate growth, development, and fulfillment for all.

Join us and be a part of a brand that inspires creativity, innovation, and passion in support of locally-owned stores around the world.

Click here to see how you can paint your future!

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
• Building predictive models or machine learning models based on the data. This includes selecting appropriate algorithms, training models, and evaluating their performance.
• Assessing the performance of the models using metrics such as accuracy, precision, recall, F1-score and model tuning to improve performance.
• • Cleansing and preprocessing raw data to make it usable for analysis. This involves handling missing values, removing duplicates, and standardizing formats.
  • Collaborate with management to prioritize Business and information needs
  • Willingness to learn and adapt to new tools, technologies, and techniques in the rapidly evolving field of data science.
  • Locating and defining new process improvement opportunities
  • Analyzing data to answer questions, identify trends, and find compelling stories within.

• Working towards degree in BA/BS and MS in Economics or Statistics, or other quantitative discipline required
• Solid grasp of microeconomic/consumer theory, experimental design, and sensitivity analysis
• Strong technical skills: Programming tools (i.e., R, Python); Cloud Software (Azure ML, Google Analytics, Snowflake); data visualization tools (i.e., Tableau, Qlik Sense); data querying tools (i.e., SQL),
• Familiarity with data science libraries and tools such as scikit-learn, TensorFlow, or PyTorch for machine learning, and Jupyter Notebook or RStudio for data analysis.
• Ability to clean, preprocess, and manipulate data using libraries like pandas in Python or dplyr in R.
• Establishes and maintains effective relationships with internal business stakeholders by fully understanding and meeting their expectations
• Creating visualizations (e.g., plots, charts, dashboards) to communicate findings and insights effectively to stakeholders.
• Documenting analysis, findings, and recommendations in a clear and concise manner. This may involve drafting reports or creating presentations.
• Excellent written and verbal communication skills with high degree of accuracy and attention to detail