Data Scientist/ Analyst

nove8

Polska

Hybrid

PLN 120,000 - 180,000

Full time

3 days ago

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Benefits offered by this job

Unlimited time off

Remote or Hybrid work

Wellness compensation

Psychologists compensation

Language courses compensation

Co-working compensation

Health insurance

Sick leave compensation

Team buildings abroad

Merch

Occasions presents

Job summary

nove8 is a young tech company building mobile apps from pet care to lifestyle, delivering meaningful digital experiences worldwide. We seek a Data Scientist/Analyst to analyze marketing, product, subscription, and financial data, focusing on long-term metrics like LTV, revenue, retention, CAC, ROI/ROMI, and payback.

You will work with large transaction-level datasets, develop predictive models, investigate data quality, and help forecast key metrics for the business.

Qualifications

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 knowledge of SQL, including experience with Google BigQuery and/or PostgreSQL
Strong knowledge of Python for data analysis and modeling, with experience using libraries such as 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
Strong 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 concepts
Understanding of subscription economics and key marketing metrics such as LTV, CAC, ROI/ROMI, payback, retention, and conversion rate
Experience working with large transaction-level and/ or event-level datasets, investigating inconsistencies and biases, and translating analytical results into business conclusions

Responsibilities

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

Skills

SQL

BigQuery

PostgreSQL

Python

pandas

NumPy

SciPy

scikit-learn

Statistics

Hypothesis testing

Time-series modeling

Survival analysis

LTV analytics

Tools

dbt

Dataform

Airflow

Tableau

Amplitude

AppsFlyer

Meta Ads

Google Ads

Job description

About Us

nove8 is a young tech company focused on mobile apps, from pet care to lifestyle. We build products that help people live, work, and connect in meaningful ways.

Today, we explore new directions, experiment, and create meaningful digital experiences for people around the world. We care about what we build and how we build it, value fairness and trust, and believe that teamwork and curiosity help us move forward together.

About the Role

We are looking for a Data Scientist/ Analyst with a strong analytical background to work with marketing, product, subscription, and financial data.

The role combines data analysis, statistics, and predictive modeling, with a strong focus on long-term marketing metrics and LTV prediction.

You will work with large-scale transactional and event-level datasets, develop and support predictive models, investigate data quality and behavioral patterns, and help the business forecast and understand key metrics such as LTV, revenue, retention, CAC, ROI/ROMI, and payback.

What We’re Looking For

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 knowledge of SQL, including experience with Google BigQuery and/or PostgreSQL
Strong knowledge of Python for data analysis and modeling, with experience using libraries such as 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
Strong 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 concepts
Understanding of subscription economics and key marketing metrics such as LTV, CAC, ROI/ROMI, payback, retention, and conversion rate
Experience working with large transaction-level and/or event-level datasets, investigating inconsistencies and biases, and translating analytical results into business conclusions

What You’ll Do

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

Nice to have

Experience with subscription-based products, recurring billing, and payment data
Experience with long-term prediction, survival / 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

Recruitment process

HR interview - Interview - Team fit interview - Offer

Our Benefits