Lauren Savage
Machine Learning Engineer (Forecasting) at DoorDash
Austin, Texas, United States
Summary
👤
Senior🎓
Top SchoolLauren Savage is a machine learning engineer specializing in forecasting with a decade of experience applying statistical rigor to real-world problems across fraud detection, targeted advertising, financial forecasting, and personalization. Currently at DoorDash, she builds production forecasting models informed by a strong academic foundation (M.S. Statistics, 4.0) and an eclectic research background spanning geophysics and astrophysics. She has held technical and leadership roles at AT&T where she automated ML solutions, authored a pending targeted-advertising patent, and delivered results that earned conference presentations and multiple hackathon wins. Comfortable across the stack—from R/Python and SQL to Spark, Hadoop, and H2O—she blends classical statistical methods with modern ML and time-series techniques. Notably, her data visualization work reached the front page of Reddit’s r/DataIsBeautiful, reflecting an ability to communicate complex insights accessibly. Based in Austin, she pairs scientific curiosity with production engineering to turn noisy data into actionable forecasts.
10 years of coding experience
7 years of employment as a software developer
Master of Science (M.S.), Statistics, 4.0, Master of Science (M.S.), Statistics, 4.0 at The University of Texas at ArlingtonCalifornia Institute of Technology
Stackoverflow
712reputation
13kreached
32answers
3questions
Github Skills (15)
r7
forecast7
apache-spark6
big-data6
avro6
hive6
pyspark6
hadoop6
python6
apache-pig6
data-science6
forecasting5
forecasts4
time-series3
forecasting-models3
Programming languages (3)
Github contributions (5)
savagedata/hurricane-animation
Sep 2017 - Sep 2017
Contributions:22 commits, 18 pushes, 1 branch in 5 days
savagedata/regression-tree-tutorial
May 2016 - May 2016
Contributions:7 commits, 20 pushes, 1 branch in 7 days
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