Hi! This is Yalo! We are on a mission to bring conversational commerce to the world...
Remember how it used to be to interact with businesses that knew and understood you, that could recommend exactly what you needed, and that with a simple message could get you what you wanted??? Yep... neither do we. That is why at Yalo we are marrying the scale of digital commerce with the personalization and simplicity of conversations to help companies delight their users.
We know that traditional SAAS companies focus on first-world problems... we don't! Having started in Latin America, our roots are in Emerging Markets and therefore we care about bringing amazing experiences to a population that traditionally has been underserved, such as the small shop owner in Brazil who is ordering online for the first time.
If you're looking for a place to make things happen, learn fast, and impact emerging markets in a way that hasn't been done before, look no further. 💫
Come Join us in our mission of improving billions of lives through the power of conversational commerce!
Your mission 🚀As a Senior Data Scientist, you will help us enhance and scale our data intelligence platform, focusing on GenAi, recommendation and personalization models by applying advanced statistical techniques, machine learning algorithms, and deep learning frameworks. You will be working closely with product, engineering, and business teams to build, integrate, and deliver successful algorithms to our state-of-the-art SaaS platform.
What are the responsibilities for this role?- Own end-to-end development of ML & AI solutions—from opportunity identification and data exploration through modeling, deployment, monitoring, and iteration that create long-term strategic advantage with clear, measurable business impact.
- Design and implement A/B experiments and causal inference analyses —conversational, behavioral, and e-commerce data— to evaluate product changes, perform statistical analysis, and clearly communicate insights and optimization impact to peers and stakeholders.
- Continuously monitor model performance, assess data quality, and refine models to ensure accuracy and reliability systems that directly contribute to product success, revenue, efficiency, or growth.
- Contribute to advancing NLP/GenAI and its applications to create highly innovative products and customer experiences, ranging from text understanding and classification to information extraction.
- Contribute to solution generation and maintenance of complex recommendation systems and their applications to deliver personalized experiences that drive key business metrics, from user preference modeling and ranking to tailored content delivery.
- Act as a strategic partner to product, engineering, and commercial teams by collaborating closely with product managers, engineers, and designers to enhance features and products through data-driven insights and analytics.
- Advocate for experimentation, explainability, and continuous evaluation of model performance in a real-world context.
Job Requirements (Must have)
- BS, or MS in an appropriate technology field (Computer Science, Statistics, Applied Math, Operations Research, Economics, etc.).
- 5+ Years of relevant experience in Data Science positions
- Experienced in Python, SQL, and AI technologies, including machine learning modeling, deep learning, GenAI systems (LLMs, prompt engineering), and NLP frameworks (PyTorch, LangGraph, sklearn, etc).
- Experienced in recommendation algorithms and marketing optimization techniques.
- Able to clearly explain complex Data Science concepts to both technical and non-technical audiences, ensuring stakeholders understand the impact and value of analytical work.
- Proven track record of working with product and engineering teams and implementing end-to-end solutions from scratch, focusing on personalization, recommendations, and customer journey.
- Experienced in designing solutions end-to-end, including defining business requirements, KPIs, effort estimates, and cost optimization strategies.
- Strives for excellence and makes it happen: proactively detects and implements improvements or new opportunities aligning with key stakeholders.
- Can work effectively within an ambiguous, ever-changing environment.
- Passion for driving continual improvement initiatives across engineering standards.
- MLOps solution exposure: SageMaker, Vertex, Azure ML, and similar tools.
- Exposure to Big Data Solutions.
- Demonstrated success in managing stakeholder expectations, milestones, and business requirements for ML products.
What do we offer?
- Unlimited PTO policy
- Competitive rewards on the market range
- Remote working is available (-+3 hours CT)
- Flexible time (driven by results)
- Start-up environment
- International teamwork
- You and nothing else limit your career here
We care,
We keep it simple,
We make it happen,
We strive for excellence.
At Yalo, we are dedicated to creating a workplace that embodies our core values: caring, initiative, excellence, and simplicity. We believe in the power of diversity and inclusivity, where everyone's unique perspectives, experiences, and talents contribute to our collective success. As we embrace and respect our differences, we strive to create something extraordinary for the benefit of all.
We are proud to be an Equal Opportunity Employer, providing equal opportunities to individuals regardless of race, color, religion, national or ethnic origin, gender, sexual orientation, gender identity or expression, age, disability, protected veteran status, or any other legally protected characteristic. Our commitment to fairness and equality is a fundamental pillar of our company.
At Yalo, we uphold a culture of excellence. We constantly challenge ourselves to go above and beyond, delivering remarkable results and driving innovation. We encourage each team member to take initiative and make things happen, empowering them to bring their best ideas forward and contribute to our shared goals.
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What We Do
Yalo helps businesses offer a delightful customer experience on their customers' favorite apps – Facebook Messenger, WhatsApp, and WeChat. Every business on Yalo has a virtual assistant with an optimized flow that handles customer requests to the point of payment and fulfillment. If at any point the customer need is beyond what the chatflow is capable of doing, the request gets seamlessly transferred to a human agent to provide resolution. Through the Yalo platform, businesses get an artificial intelligence powered CRM that allows them to handle sales and build personal relationships, at scale, on Facebook Messenger, WhatsApp, and WeChat.
Yalo uses deep learning (a machine learning technique) to have chatbots learn from their human counterparts to continuously improve the experience. The team behind Yalo is composed of Columbia University and Salamanca engineers, former PayPal technical leads, and is supported by a group of investors from New York, Mexico and Latin America.
