Adam J. Baron is the Director of Big Data Quantitative Research for the StarMine Quantitative Research Team at Refinitiv. For the past few years he’s worn the hat of a full stack data scientist that is hands on during the entire process: from identifying potential data sources to the necessary rigors of big data engineering to the final stage of quantitative model research. His alternative data journey has allowed him to dive into many interesting content sets in search of alpha such as footfall derived from mobile phone GPS, credit/debit card transactions, satellite images, retail product pricing, trucking fleet vehicle telematics, job postings, text and ESG. These diverse data sets require a diverse set of technologies, top among them being AWS (SageMaker, Glue, Athena), GCP (BigQuery, TPUs), Azure, Hadoop/Spark, Python, R and SQL. Prior to joining Thomson Reuters (now Refinitiv), Adam spent the earlier part of his career working on Wall Street in FinTech at Morgan Stanley. During that time he earned an MBA from NYU Stern in the evenings, sparking a new career passion for quantitative finance that nicely complemented his computer science background from undergraduate studies at Rensselaer Polytechnic Institute.