Hire Top-Tier Nearshore Data Scientist in LATAM

Technical Questions

• • Design an A/B testing framework for a marketplace that has network effects between buyers and sellers. How would you handle contamination and measure true causal impact?
• • You're building a churn prediction model for a subscription business. Walk me through your approach: feature engineering, model selection, evaluation metrics, and deployment strategy.
• • How would you approach measuring the causal impact of a marketing campaign using observational data? What techniques would you use to control for selection bias?
• • Explain how you'd build a recommendation system for a cold-start problem where you have limited user interaction data. What strategies would you consider?
• • You have a dataset with significant class imbalance (1:50 ratio) and the minority class is the one you care about predicting. How would you approach this problem?
• • Describe your experience with time series forecasting. When would you choose ARIMA vs. Prophet vs. LSTM, and how do you evaluate forecast quality?

Cultural Fit Questions

• • Tell me about a data science project where your initial hypothesis was completely wrong. How did you pivot and what did you learn?
• • Describe a situation where you had to balance statistical rigor with business timelines. How did you make tradeoffs?
• • How do you approach stakeholder management when your analysis reveals uncomfortable truths about the business?
• • When you discover a data quality issue that affects a production model, what's your process for investigating and fixing it?

Current Trends

• Data science roles grew 72% year-over-year in LATAM as companies move from descriptive analytics to predictive modeling and causal inference. Demand for experimentation expertise increased 95%.
• ML skills are now baseline: 89% of data scientist postings require production ML experience, up from 58% in 2023. Pure BI/analytics roles are declining as ML becomes expected.
• Domain expertise commands significant premiums: data scientists with vertical knowledge (fintech, healthcare, e-commerce) earn 30-40% more than generalists.

Demand Factors

• U.S. shortage of data scientists with business acumen: 45,000+ open positions vs. 18,000 candidates with 4+ years of stakeholder-facing experience.
• LATAM data scientists bring bilingual communication advantage: 85% have B2+ English proficiency, critical for explaining complex findings to executive teams.
• Real-world experience at scale: LATAM data scientists have built models for companies processing tens of billions in transactions, proving capabilities matching top U.S. tech companies.

15,000+ Talent Pool

Access our curated database of senior LATAM professionals. Every candidate is pre-screened for English (B2+), technical skills, and remote work readiness.

AI Screening (Stage 1)

Our AI analyzes your requirements and screens 15,000+ candidates against tech stack, timezone, experience, and culture fit. Only 500 pass to the next stage.

Human Expert Review (Stage 2)

Senior recruiters conduct live interviews verifying bilingual communication (English/Spanish), technical depth, and culture fit. Only the top 3% make it to your shortlist.

48h Shortlist

Receive 3-5 AI & human vetted profiles with video intros, code samples, and detailed assessments. Schedule interviews directly with top candidates.

Offer Management

We handle salary negotiations, contract setup, and compliance. You focus on evaluating fit—we handle the paperwork and logistics.

Risk-Free Start

Start with a paid trial period. If the hire doesn't work out, we replace them at no cost. 95% of our placements convert to long-term hires.