Staff Data Scientist
LATAM
Yalo Inc.
Sell more, engage, and build deep relationships through Conversational Commerce on WhatsApp and other messaging apps.Yalo
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 Staff Data Scientist, drive measurable business impact by designing, developing, and deploying advanced data science solutions. Act as a strategic partner to product, engineering, and commercial teams by translating complex business problems into scalable AI/ML systems that power AI agents, personalization, recommendations, and intelligent decision-making across the platform.
What are the responsibilities for this role?
- Owns the data science strategy for a major domain or product area, ensuring all solutions are deeply tied to business outcomes.
- Partner directly with stakeholders (Product, Marketing, etc) to proactively identify, scope, and complete high-impact modeling opportunities, raising the bar for technical excellence and business/product thinking.
- Mentor data scientists and machine learning engineers across the team, guiding technical development, model design, and implementation strategies.
- Serve as a trusted thought partner in quarterly and annual planning, helping define the data science strategy, investment roadmap, and team evolution.
- Lead and 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.
- Architect model governance standards and MLOps and LLMOps best practices in partnership with Data & ML Engineering, including model registration, reproducibility, retraining workflows, performance monitoring, and alerting.
- Design, plan, implement, and analyze A/B experiments, and conduct causal inference analysis to evaluate product changes.
- Perform deep-dive analyses to identify product growth opportunities and drive improvements in core business metrics.
Job Requirements (Must have)
- BS, MS in an appropriate technology field (Computer Science, Statistics, Applied Math, Operations Research, Economics, etc.).
- 8+ years of experience delivering end-to-end data science solutions with measurable business impact in cross-functional teams.
- Expert in Python, SQL, and AI technologies, including machine learning modeling, deep learning, GenAI systems (LLMs, prompt engineering), and NLP frameworks (Pythorch, LangGraph, sklearn, etc).
- Strong knowledge of ML/AI infrastructure and production ML pipelines (CI/CD, Airflow, MLflow, Kubeflow).
- Experienced in recommendation algorithms and marketing optimization techniques.
- Familiar with AI safety and responsible AI development practices.
- Skilled at translating complex technical concepts into clear insights for both technical and non-technical stakeholders.
- Strong product and business acumen, capable of framing problems from a user and commercial perspective.
- Excellent communication and creative problem-solving skills.
- Proven track record of delivering end-to-end data science solutions with measurable business outcomes, working with collaborative, cross-functional teams.
Nice to have:
- 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.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: A/B testing Airflow Azure Big Data Causal inference CI/CD Computer Science Deep Learning Economics Engineering Generative AI Kubeflow LLMOps LLMs Machine Learning Mathematics MLFlow ML infrastructure MLOps Model design NLP Pipelines Prompt engineering Python Research Responsible AI SageMaker Scikit-learn SQL Statistics Vertex AI
Perks/benefits: Career development Flex hours Flex vacation Startup environment Unlimited paid time off
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