DataKind is looking for a Machine Learning Engineer!

DataKind is looking for a values-driven Machine Learning Engineer who is ready to make a major impact on student graduation rates by building and maintaining machine learning pipelines to help us deliver on our next decade of data science solutions for positive social impact. If you’re a problem-solver eager to embrace challenges as opportunities, you’re a strong collaborator who delights in creating the infrastructure to enable data science, and you are a detail-oriented machine learning engineer committed to advancing equity, we want to bring you on board!  

Location

Remote position available anywhere in the U.S. with working hours primarily between 8am-6pm Eastern Time.

Salary Range
The salary range is $106,000 - $120,000

This salary range reflects DataKind's standardized compensation bands for technical, manager level positions. Our compensation structure is designed to ensure internal equity and competitive market alignment regardless of geographic location within the U.S.. The final salary offer within this range will be determined based on relevant experience, expertise, and qualifications as they relate to the role requirements, not candidate location.

About the Opportunity 

DataKind has developed an innovative predictive analytics platform (Student Success Tool) that empowers academic advisors to identify at-risk students and dramatically improve graduation rates through targeted interventions. Our groundbreaking work has been featured in the New York Times, and we're now entering a critical growth phase.

Reporting to the Director of Data Science, Education, the Machine Learning Engineer will be responsible for maintaining data management systems and deploying machine learning models within those systems. You will provide direct guidance and support to schools and partners in how to share data with DataKind with appropriate data structure and governance measures in place. The Machine Learning Engineer will own the design and implementation of data architecture, pipelines, validation, and security. In this role, you’ll work closely with other Technology team members as well as our Product and Research teams.

Core Responsibilities

The Machine Learning Engineer will be responsible for the following in addition to any other project assigned by the Director of Data Science:

Design, build, test, and maintain machine learning pipeline architectures (70%)

• Produce high-quality, reusable code for data ingestion, validation, and processing pipelines
• Architect and implement end-to-end ML pipelines including training, retraining, and inference systems for schools using the SST
• Design and build APIs to easily access, integrate, and manage data from different sources
• Ensure data infrastructure is in compliance with data governance and security policies
• Create comprehensive documentation for data infrastructure and ML pipelines, tailored for both technical and non-technical stakeholders
• Advance internal analytics reporting and automation capabilities as needed

Provide direct data support to partners (15%)

• Manage initial data lifecycle processes for new school onboarding including ingestion, transfer, audit, and validation
• Collaborate with data platform partners on integration and data transfer pipelines
• Provide technical guidance to partners on how to share data formatted in alignment with our data model and with appropriate data governance measures 
• Address partner concerns regarding data security and ensure their specific requirements are satisfied
• Support data science initiatives through processing, cleaning, and analyzing data as needed

Collaborate and contribute across DataKind (15%)

• Support other data team members through code reviews and knowledge sharing across products
• Collaborate with the Product, Engineering, and Research teams to ensure seamless integration and alignment of work
• Effectively communicate project status and manage expectations with internal teams and partner organizations
• Maintain accurate and current project information in project management tools like Asana

Qualifications 

Required

• Alignment with DataKind’s mission and values, including our commitment to anti-racism
• Experience working across lines of difference (culture, identity, and time zone)
• At least 3 years of professional work experience in developing and deploying a machine learning product at scale
• Foundational understanding of machine learning and statistical methods for predictive modeling
• Expert in Python
• Experience with cloud computing (GCP preferred)
• Experience with databases (SQL, Postgres, PySpark, and/or other data query languages)
• Experience with DataBricks or a similar data intelligence platform
• Experience with data warehousing, orchestration, integration, and ETL tools
• Experience with modern source code management and software repository systems (i.e. Git)
• Experience documenting and implementing RESTful APIs
• Proven track record of successfully managing full life-cycle machine learning implementation projects with multiple stakeholders
• Solid understanding of Software Engineering principles and best practices and the data science project life-cycle
• Comfort and skill in communicating highly technical information to semi- and non- technical audiences
• Self-motivated, results-driven, and persistent in the face of challenges

Preferred 

• Experience integrating data from SaaS providers
• Experience in the nonprofit sector and/or in a small startup organization
• Experience in scaling machine learning products, handling data quality and volume 
• Certifications in cloud computing
• Advanced experience in machine learning—confident in applying, tuning, and evaluating a wide variety of algorithms 
• Experience with software development and/or web-dev work (frontends, dashboards, etc.)
• Track record of strong technical writing for a variety of audiences
• Proven track record of (internal or external) client service orientation

About DataKind

DataKind, we believe in the transformative power of data science and AI to create a more promising future. Since our founding in 2012, we’ve been at the forefront of designing scalable, data-driven tools that address some of the world’s toughest challenges—ranging from frontline health, humanitarian action, climate and environment, economic opportunity, education, and more. As both a product innovator and a movement catalyst, we set new standards in the social sector, empowering organizations to harness the full potential of data science and AI while putting communities first.

Why Work with DataKind

At DataKind, we believe that people are the most important asset to delivering on our mission. As a people-first remote organization, we offer the following for all our employees:

• Flexibility and time off. Enjoy genuine flexibility that goes beyond adjustable hours. We build in shared time off, company-wide recharge days, bi-weekly meeting-free days, and flexible PTO (with a minimum of 20 vacation days encouraged annually).
• Comprehensive Wellness Support. We care for your total wellbeing with 100% employer-paid medical, vision, and dental benefits for employees (72% for dependents), a wellness reimbursement program for the activities and purchases that matter to you, and 12 weeks paid parental leave when you need it most.
• A Culture of Growth. Every team member receives professional development funding each year, alongside mentorship and advancement opportunities. We invest in your future with a 401(k) plan with 5% employer matching. 
• Meaningful Connection. Despite being distributed across time zones, we value being able to come together in person for conferences, strategic planning, and at our annual staff retreat. 
• Living our Values. DataKind is committed to a diverse, equitable and inclusive work environment in our day-to-day work and via special initiatives driven by our DEI Steering Committee.

 

Encouraging Applicants of All Backgrounds

We encourage people from all backgrounds to apply, especially people of color, people with disabilities, veterans, and members of the LGBTQ+ community. 

DataKind is an equal opportunity employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status, genetic information, pregnancy, or any other category/characteristics protected by law. No matter one’s background, the new Vice President, Development must value and advocate for inclusion and equity.

Applicants must have a U.S.-based permanent address and be currently authorized to work in the United States on a full-time basis  indefinitely without employer visa sponsorship.