Analyst (Operations Research Analyst)

Job Description:

·       Identify opportunities to use data to develop new strategies and utilize knowledge of mathematical modeling and other optimization methods to perform quantitative and qualitative data analysis.

·       Gather, analyze and interpret a wide variety of data to identify casual relationships, trigger points and ultimately make predictions on customer behavior.

·       Create report and perform analysis on business trends and projects, including, but not limited to, comparing results to previous trends, evaluating and explaining new trends, drawing conclusions, and making recommendations to stakeholders.

·       Build predictive models using data, test the model on results outside of the sample size and verify the model in the real world.

·       Quantify significance of data variance, apply an array of statistical methods ranging from traditional to newly-developing within he Big-Data space.

·       Develop reports, charts, tables and other visual aids in support of findings.

·       Turn complex data into practical, actionable and understandable marketing insights data.

·       Communicate with teams on a regular basis and assist in development of department goals and strategies.

·       Advise business partners with regards to patterns and relationships in data to recommend business direction or outcomes.

·       Prepare and present business cases for optimization initiatives, trial success or failure.

·       Research new reporting topics to gain a full understanding of how the resulting data flows through the data warehouse for accurate reporting.


·       Bachelor's degree (or equivalent) in Mathematics, Computer Science or closely related specialized & advanced Quantitative field of study.

·       Expert in large distributed datasets using Shell Scripts, Apache, Python.

·       Advanced SQL skills.

·       Knowledge of Tableau AND Power bi.

·       Experience quantifying significance of data variance and applying statistical methods.

·       Knowledge and understanding of data mining and statistics concepts and familiarity with real-world applications of these techniques.

·       Strong written and verbal communication, presentation, client service and technical writing skills for both technical and business audiences.

·       Strong analytical, problem solving and critical thinking skills.

·       Strong attention to detail, with a quality-focused mindset.