Data Scientist

Overview

Data Scientist

Responsibilities Include

Statistical analysis and predictive modeling. Own process end-to-end: implement statistical methods and build, train, and deploy predictive models to solve problems in cash delivery utilizing code (e.g., Python, R). Current priorities:
Targeting. Implement and improve existing machine learning algorithms predicting poverty level from call-detail records (CDR) and geospatial data. This work enables us to remotely identify eligible recipients at scale, and has been highlighted in WIRED with findings published by our research partners in Nature.
Risk prediction. Develop new risk prediction models that help us design programs and target recipient outreach to keep recipients and communities safe.
Support data quality assurance. Work with the Senior Data Architect to design processes that ensure key metrics, models, and analysis are built on high quality data.
Communication. Collaborate with leaders throughout the organization to define data product requirements, educate them about solutions, and make recommendations.
This role has a high degree of autonomy and the ability to shape our process from the ground up by determining best practices and informing the data product roadmap.

You are an analytical problem solver who knows how to:

Frame a testable question from ambiguous requirements
Gather, lean, and manipulate the required data
Deliver answers that directly inform important decisions

You Deliver Results That Impact Real-world Outcomes By

Solving for user needs and constraints
Understanding when to build complex models and when simpler solutions are more appropriate
Communicating takeaways clearly
You are intellectually curious and humble. You think probabilistically and measure the uncertainty of your predictions.

You are a mid-level to Senior Data Scientist with the following qualifications.

Required Qualifications

5+ years experience working with data querying languages (e.g., SQL) and statistical modeling software (e.g., Python, R)
5+ years experience as a Data Scientist or related position applying statistical and/or machine learning (ML) techniques, with a deep understanding of the key parameters that affect their performance
Deep understanding of ML algorithms – ability to apply the appropriate methods, as well as benchmark and diagnose predictions to rapidly improve performance
Proficient in spark, dask, and/or other packages for distributed computing
Ability to travel and deploy to international, on premise locations for up to 1 month at a time

MODE OF APPLICATION

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