nove8 is a tech company focused on mobile apps. The role works with marketing, product, subscription, and financial data, combining data analysis, statistics, and predictive modeling, with a focus on long-term marketing metrics and LTV prediction.

Responsibilities:

  • Develop, validate, improve, and support prediction models for LTV, revenue, and retention.
  • Design and maintain time-based validation and backtesting approaches.
  • Work with incomplete and censored cohort data, accounting for cohort maturity.
  • Investigate transactional and event-level data, validate data semantics, and identify data quality issues.
  • Monitor model performance, diagnose prediction errors, and improve model quality.
  • Build and maintain datasets and features, and support A/B test analysis and statistical interpretation.
  • Bring models from research into scheduled production calculations and expand modeling to other areas, including risk models.

Requirements:

  • 2+ years of experience as a Data Scientist or Data Analyst, or demonstrated experience delivering an end-to-end analytical or predictive modeling project.
  • Strong SQL skills, including Google BigQuery and/or PostgreSQL.
  • Strong Python skills for data analysis and modeling; experience with pandas, NumPy, SciPy, scikit-learn, or statsmodels.
  • Strong understanding of mathematics, probability, statistics, statistical inference, and hypothesis testing.
  • Understanding of classical statistical and machine learning approaches and experience building predictive models.
  • Understanding of model validation, including time-based validation, backtesting, data leakage, overfitting, and model stability.
  • Understanding of censored and incomplete data, cohort maturity, and basic survival analysis.
  • Understanding of subscription economics and metrics such as LTV, CAC, ROI/ROMI, payback, retention, and conversion rate.
  • Experience with large transaction-level and/or event-level datasets, investigating inconsistencies and biases, and translating analysis into business conclusions.

Nice to have:

  • Experience with subscription products, recurring billing, and payment data.
  • Experience with long-term prediction, survival or hazard models, or other time-dependent modeling approaches.
  • Experience with Stripe, PayPal, or similar payment providers.
  • Experience with dbt / Dataform, Airflow, Tableau, Amplitude, AppsFlyer, Meta Ads, or Google Ads.
  • Familiarity with production ML workflows, model monitoring, retraining, and common classical ML models.

Conditions and benefits: Full-time; remote or hybrid, with the choice of work arrangement. Benefits include unlimited time off, wellness and psychologist compensation, language courses, co-working compensation, health insurance, 100% sick leave compensation, team buildings and offsites, and merch and special occasion gifts.