Sr. Data Scientist, Machine Learning

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About PulsePoin t:
PulsePoint is a fast-growing healthcare technology company (with adtech roots) using real-time data to transform healthcare. We help brands and agencies interpret the hard-to-read signals across the health journey and unify these digital determinants of health with real-world data to produce the most dimensional view of the customer. Our award-winning advertising platforms use machine learning and programmatic automation to seamlessly activate this data, making marketing, predictive analytics, and decision support easy and instantaneous.

Description
Our Data & Analytics team is at the very heart of what makes PulsePoint an innovative, fast-paced and market-changing company.

Our path forward is through data and this team is in the driver seat for the journey.

The Big Picture :
You will build, deliver & continually innovate on PulsePoint's insightful reporting and data-driven solutions. Your efforts help alleviate friction points and streamline processes that enable internal teams to provide exceptional service, powering the decisions of our customers.

In short, you will be the conduit through which we will revolutionize health decisions through real-time data. As a Sr. Data Scientist, R&D , you will use your data science and stats expertise to contribute to R&D projects for DTC, new Data Products, and Bespoke Segments expansion.

Specifically, here are some things we’ll want you to get done:
Data science & stats-related projects
Work on R&D projects for DTC
Help build new Data Products
Contribute to Bespoke Segments expansion
Help us design and define the methodology for our measurement products and user identification
Continuously improve the quality of HCP onboarding/Targeting/measurement
Audience IQ/DTC product development, Identity graph/Data IQ
Collaborate with internal teams to delight our customers with timely and accurate data reporting that meets all requirements;
Research & implement new data products or capabilities
Automate data visualization and reporting capabilities that empower users (both internal and external) to access data on their own thereby improving quality, accuracy, and speed
Synthesize raw data into actionable insights to drive business results, identify key trends and opportunities for business teams, and report the findings in a simple, compelling way
Evaluate and approve additional data partners or data assets to be utilized for identity resolution, targeting, or measurement
Enhance PulsePoint's data reporting and insights generation capability by publishing internal reports about Health data
Act as the “Subject Matter Expert” to help internal teams understand the capabilities of our platforms, how to implement & troubleshoot

Requirements
Required qualifications:
~4-5+ years of relevant experience in:
~ Creating SQL queries from scratch using real business data;
~ Highly proficient knowledge of Excel (pivot tables, VLOOKUP, formulas, functions)
~ Data analysis & manipulation
~ Python
~ At least a Bachelor’s degree in Business Intelligence and Analytics or closely related field
~ Knowledge of Distributed Systems. PySpark , for large-scale data processing.
~ Experience with Containerization (Docker) and Kubernetes
~ Proven experience of experimentation methods and Stats modeling in support of product development and optimization
~ Willing and able to work 3:30pm-12:30am IST, you can work fully remotely

Preferred qualifications:
And one of:
ELT experience
Tableau/Looker/PowerBI
Experience with automation
Able to organize large data sets to answer critical questions, extrapolate trends, and tell a story
Experience in Programmatic/Adtech
Familiarity with health-related data sets
Google Cloud Architecture

What are ‘red flags’ for us :
Candidates won’t succeed here if they haven’t worked closely with data sets or have simply translated requirements created by others into SQL without a deeper understanding of how the data impacts our business and, in turn, our clients’ success metrics

Selection Process :
1) Online SQL Test (35 mins)
2) Initial Screen (30 mins)
3) Hiring Manager Interview (30 mins)
4) Data Science Manager Interview (30 mins)
5) Interview with Sr. Data Scientists (30 mins)
6) Interview with SVP of Data (30 mins)

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