The Role
At ASAPP, our mission is simple: deliver the best AI-powered customer experience—faster than anyone else. To achieve that, we’re guided by principles that shape how we think, build, and execute. We value customer obsession, purposeful speed, ownership, and a relentless focus on outcomes. We work in tight, skilled teams, prioritize clarity over complexity, and continuously evolve through curiosity, data, and craftsmanship.
We’re seeking technologists and problem solvers who thrive in fast-paced environments, love collaborating with great talent, and approach every day like it’s Day 1. We're a globally diverse team with hubs in New York City, Mountain View, Latin America, and India—embracing both hybrid and remote work to bring the best minds together, wherever they are. If you're driven by continuous learning, rapid pivots, and the challenges of building in a high-growth startup, we’d love to talk. This is more than a job—it’s a journey.
In this role, you will apply techniques from machine learning and modern statistics to data from ASAPP products and our customers. You will identify questions, and develop and apply approaches to solve problems that are central to our product and our customers.
If you love an environment of deep thinking, impactful research, startup-paced execution, and strong collaboration with all parts of an organization, ASAPP is an ideal environment for you. Please note that we are looking for candidates in and around Buenos Aires, who would be open to some occasional in person work.
What you'll do
- Use modeling to develop a deep understanding of how our product provides value to our customers, and to identify and quantify opportunities for creating additional value
- Collaborate with Product and Tech teams to evaluate the effectiveness of current features, and identify new opportunities
- Work with a broader team of researchers, engineers, product managers, and customer-facing groups
- Develop experimental designs to answer questions, and perform analysis of the results
- Apply causal inference approaches to maximize the data we have on hand
What you'll need
- Ability to present data science results and recommendations to cross-functional teams
- Expertise in modern statistics/data science/machine learning
- Expertise in a statistical programming language (we use Python and R internally) and data access tools (e.g., SQL)
What we'd like to see
- Experience with machine learning (e.g. xgboost, generalized linear models, additive models, clustering, factorization machines, etc), deep learning (PyTorch a plus), statistics (experimental design, estimation, testing), and LLMs
- Graduate Degree with a background in statistics and machine learning, and/or applied social sciences or equivalent work experience
- Ability to maintain a fun, casual, professional, and productive team atmosphere
- Communication in a courteous, tactful, and concise manner
- Enthusiasm and desire to thrive in an atmosphere of constant change
Benefits
- Competitive compensation
- Stock options
- Healthcare for the family group
- Wellness perks
- Mac equipment
- Learning & development stipend
- 3 weeks of vacation
- English lessons
ASAPP is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, disability, age, or veteran status. If you have a disability and need assistance with our employment application process, please email us at [email protected] to obtain assistance. #LI-SL1 #LI-Remote
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The Company
What We Do
Our artificial intelligence and machine learning products deliver automation and human augmentation, allowing individuals and organizations to realize their full potential. Today, the world's largest organizations rely on ASAPP to provide amazingly efficient and effective customer experiences. Our Research & Development team is unparalleled, driving the advancement of AI, machine learning, speech recognition, robotic process automation, natural language processing and more.
