Científico(a) de Datos Sénior

We Make Remote Work Remarkable • TopTalent from LatAm

Hello! We are GoFasti, a Talent-as-a-Service. GoFasti bridges the gap between world-class developers and designers from LatAm and first-class companies around the globe.

We need an English-fluent Senior Data Scientist, based in Latin America, available to work remotely.

We are looking for someone with exceptional communication and relationship-building skills, who embraces changes while maintaining strong attention to detail. An interested and proactive person, who's constantly learning and improving their skills.

Are you the one we are looking for?

Responsibilities:

• Develop, deploy and maintain predictive models for lifetime value (LTV), churn and retention across mobile apps and web/browser products

• Own the modeling roadmap for your area, from problem framing through production and ongoing monitoring

• Build cohort and LTV models that inform user acquisition budgets and payback decisions

• Build user segmentation and propensity models that support personalization and targeting

• Improve model accuracy over time through validation, backtesting and new data sources

• Design experiments and causal analyses that measure the true impact of product and marketing changes

• Identify early behavioral signals that predict conversion, churn and long-term value

• Apply LLMs and machine learning to classify unstructured text and behavioral signals into interest categories and product and brand intent

• Partner with data engineering to productionize models and keep their inputs reliable

• Build internal AI-powered analytics tools and data products

• Explain model results, assumptions and confidence levels clearly to stakeholders and leadership

• Set modeling standards, documentation and best practices for the team

• Mentor other analysts and data scientists and share best practices across the team

Requirements:

• 5+ years of experience in data science, statistical modeling or machine learning, ideally with consumer app or web data

• Strong Python (pandas, scikit-learn or similar) and advanced SQL

• Experience deploying models to production and monitoring them over time

• Solid grounding in statistics, forecasting and experimentation

• Hands-on experience with LLM APIs, prompt design or building AI-powered data tools

• Daily use of AI tools as a development partner, such as Claude, Claude Code or Claude Cowork

• Sound judgment with incomplete or noisy data; you structure the problem before reaching for a tool

• Strong communication skills, including turning complex analysis into clear business recommendations

• Fluent English and at least 4 hours of overlap with US Eastern business hours (remote roles)

It's a plus:

• Experience with ad-monetized or subscription consumer apps

• Experience with recommendation systems, personalization or audience segmentation for ad targeting

• Experience with ML platforms on AWS or Google Cloud, such as SageMaker or Vertex AI

• Familiarity with MLOps and orchestration tools such as MLflow, Airflow or dbt

• Familiarity with Bayesian methods, uplift modeling or multi-armed bandits

Compensation:

• The salary range offered for this position varies from (USD) $4,000 - $5,500 per month, depending on seniority and skillset.

• This position is for a full time contract, through a payroll platform.

• The talent will work remotely allocated at our client.

Here are the steps for this process:

TBD > Application review/approval > Screening interview with GoFasti's team > We build and send your profile to our client > Profile review/approval by client > Interview with the client > Hiring and onboarding.

Once you apply for the job, our team will review your resume. If it meets the requirements, we will contact you and move forward in the process. 

Note for Candidates Approached Directly:
If you were contacted directly by a member of our team and are interested in this opportunity, please do not apply through this link. Instead, reach out to the person who contacted you to coordinate a meeting.

Thank you!