Machine Learning Engineer, Auction Mechanics

Company: PulsePoint
Location: New York
Posted on: January 16, 2022

Job Description:

Description

PulsePoint's award winning platforms accelerate data and programmatic technology to deliver contextually relevant and personalized health information. We help brands and agencies better understand audience engagement and are revolutionizing health decisions through real time data.

As a member of our Data Science Engineering team, the Machine Learning Engineer, Auction Mechanics , will focus on the following:

Optimizing real-time bidding strategies and auction mechanics to efficiently spend ad budgets and deliver against campaign targets;

In addition to the above, they will work with the greater Data Science/Engineering teams on:
Improving existing or developing new traffic segmentation algorithms and estimations of bid landscapes within each segment;
Supporting and enhancing the existing work on health user profiling, prediction, and targeting tools;
Contributing on projects relating to patient/physician identity for cross-device tracking, profiling and targeting;
Supporting existing codebase for data integration and production support for our core models.
Improving page contextualizer technology: work with healthcare topics detection algorithms, keywords/phrases extraction, general and aspect-based sentiment analysis.

Requirements

These are the things that we'll be looking for from a candidate:
5+ years of RTB Auction or similar experience; (Note--Please provide detail on this important requirement in your cover letter).
Advanced knowledge of Python using numpy & pandas;
Being able to optimize and speed up code.

In Addition To The Above, You'll Need To Have Strong Knowledge In The Following Areas (along With a Breakdown Of The Areas We'd Like For You To Have Exposure With)
Algorithms and Data Structures--Sorting, search tree, binary heap, trie; Time & mem complexity of algorithms.
Probability & Statistics-Markov processes and its stationary distributions; Stochastic matrix and properties of its eigenvalues; Bayesian inference and conjugate distributions; Two-sample hypothesis testing.
ML & DS--Dimensionality reduction; Geometry of PCA and SVD; Geometry of L1 and L2 regularisation (Why does L1 result in feature selection?); Decision Trees; Collaborative filtering; Thompson sampling; MCMC; Boosting, (Biases in Boosted DT); Bagging
Neural Networks--Embeddings; Encoders; Drop-out; CNN, RNN; Internal covariate shift.

Benefits
Comprehensive healthcare with 100%-paid medical, vision, life, & disability insurance
401(k) Match
Generous paid vacation and sick time
Vacation reimbursement (we give you $500/year to take vacation), marriage leave
Paid parental leave, new parent perks, & adoption assistance
Annual training and development budget & annual tuition assistance
Donation matching and group volunteer opportunities
A referral bonus program -- we love hiring referrals here at PulsePoint

And there's a lot more!

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Keywords: PulsePoint, New York , Machine Learning Engineer, Auction Mechanics, Engineering , New York, New York