Senior Growth Data Scientist: LTV & Acquisition Analytics

ARQ; New York (NY); Hybrid; USD 140,000 - 210,000; Full time

Benefits offered by this job

Competitive salary

Stock options

Performance bonus

Latest tools and technology

World-class team

Fintech app LATAM

In-office 3-4 days

Job summary

ARQ is seeking a Senior Data Scientist to own data science across Growth and Marketing. You’ll build and refine LTV prediction models across four countries and acquisition channels, informing growth investment, channel performance, and long-term customer value.

You’ll collaborate with Growth, Marketing, Product, Finance, and Engineering, translating ambiguous business questions into measurable modelling problems and delivering impactful solutions with high ownership.

Qualifications

• 5+ years in Data Science, ML, Applied Statistics, Analytics, or related discipline.
• Experience building prediction models in consumer business (B2C, D2C) around LTV/growth/retention.
• Strong Python skills with large-scale datasets.

Responsibilities

• Design and maintain lifetime value prediction models across ARQ’s countries and channels.
• Collaborate with Growth, Marketing, Product, Finance, Data Eng., and Engineering to translate needs into modelling solutions.
• Monitor model performance and impact; improve accuracy and business outcomes over time.
• Produce frameworks and metrics to explain trade-offs of growth decisions.
• Partner with Eng and Data Eng to productionise models, pipelines, and reporting.

Skills

Data Science

Python

LTV modelling

Cross-functional

Communication

English

Problem Framing

MLOps

Model evaluation

Job description

ARQ is seeking a Senior Data Scientist to own data science across Growth and Marketing. You’ll build and refine LTV prediction models across four countries and acquisition channels, informing growth investment, channel performance, and long-term customer value.

You’ll collaborate with Growth, Marketing, Product, Finance, and Engineering, translating ambiguous business questions into measurable modelling problems and delivering impactful solutions with high ownership.