Providing hyper-local data on communities around the world
Our company has pioneered the use of geospatial data to understand population dynamics. Governments and organizations around the world rely on Fraym data to make strategic and operational decisions while tackling challenges like inequity and insecurity, climate vulnerability, public health, and more. Our advanced AI/ML models are the first to generate high-resolution insights about human characteristics and behaviors at the sub-neighborhood level and make them commercially available at scale.
Summary of Position:
Fraym is seeking a Data Science Team Lead to help their team grow a portfolio of analytical product offerings and improve predictive algorithms in a small data context. Your contributions will support decisions made in emerging markets across international development and intelligence sectors. Your work will be split between people management (50%) and technical leadership (50%) responsibilities.
You enjoy managing a team that builds client-driven solutions from data wrangling to delivered products. You should have a strong data science background and experience working with geospatial data, libraries, and software. Preference will be given to applicants with experience in growing teams as well as algorithm design and/or analytic solutions.
● Managing a small, talented team of ML engineers and data scientists who are responsible for creating and deploying new methods to meet existing client needs.
● Collaborating with data science team leadership to determine, drive, and pivot the data science team and overall Fraym vision
● Coordinating with our data analytics team in the execution of data science workflows
● Contributing to the development of product offerings and capabilities such as machine learning applications, data subscription packages, and inventive data visualizations
● Developing workflows and identifying new applications of methodologies for company-initiated use-cases leveraging multiple data sources, as well as generalizing methodologies developed in-house
● Managing and growing research projects from inception to full scale workflows, products, and applications in coordination with data engineers and data architects
● Bachelor’s or master’s degree in a related field
● At least 3 year of working in a data science context, including people management in a data science, or adjacent, industry
● Proven ability to mentor and guide the professional trajectory of individuals they have managed
○ Working in the nitty gritty of Machine Learning modeling, including applying suitable best practice techniques for model testing, tuning, accuracy, and validity
○ Python (geopandas, sklearn, numpy, etc.) and/or R (raster, tidyverse, caret, etc.)
○ cloud computing environment (AWS).
○ Git, version control
● GIS / geospatial tools (Arc/Q, gdal/rasterio, raster package)
● Communicating methodology to non-technical audiences
● Knowledge management experience
● Formal training or experience in project management best practices (such as Agile)
● Experience working with or in the intelligence sector
Working at Fraym:
● Competitive, market-based salary commensurate with experience, including base salary and annual performance bonus
● Professional development and learning opportunities
● Stay healthy and happy through our comprehensive medical, dental and vision insurance including other ancillary benefits
● Save for the future with our 401(k) program
● Health & Wellness stipend for self-care
● Take time away from the office through our Flexible Paid Time Off
● We are committed to fostering a positive work-life balance culture
● Be a part of a community and take part in our lunch & learns and team outings
● We are a “Growth Culture” that provides opportunities for career advancement and professional development in a fast-growing company
Not sure you tick all the boxes? We encourage you to apply. We have a culture of learning, and if this job description sounds exciting, we’d love to hear from you.
Fraym recruits, employs, trains, compensates and promotes regardless of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, family status, veteran status, and other protected status as required by applicable law.
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