Lead Data Scientist

Datacontroller Toogeza Ltd.; United States; Remote; USD 140,000 - 210,000; Full time

Benefits offered by this job

25 vacation days + 15 sick days + 1a0

Birthday leave

Budget for English classes

Budget for health insurance

Annual education & development budget

Remote-friendly culture

Job summary

SpinLab is seeking a Lead Data Scientist to drive scalable ML solutions with hands-on coding, technical leadership, and product thinking. You will collaborate with product and business teams to translate problems into data science work, define success metrics, and deploy models that impact revenue and player behavior.

Responsibilities include designing scalable DS/DA processes, ensuring production readiness, and advancing experimentation frameworks.

Qualifications

• Bachelor’s or Master’s degree in Statistics, Mathematics, Computer Science, Economics, or a related quantitative field.
• 5+ years of experience as a Senior Data Scientist or Lead role, leading both analytical and data science domain work.
• Strong SQL and Python skills; experience with large datasets, notebooks, reproducible analysis, and Git-based workflows.
• Solid knowledge of ML, statistics, experimental design, A/B testing, holdout evaluation, and business KPI analysis.
• Commercial experience with predictive modeling, classification, segmentation, forecasting, model evaluation, and business impact measurement.
• Experience with churn, uplift, LTV, retention, campaign analytics, or user behavior modeling is a strong advantage.
• Strong analytical and problem-solving mindset; ability to tell stories with data and explain trends in business terms.
• Commercial experience working with large datasets and distributed computing tools (BigQuery, Spark, Hive, or similar).
• Familiarity with causal inference techniques (Propensity Score Matching, Instrumental Variables, Difference-in-Differences, uplift modeling) and predictive modeling.

Responsibilities

• Work closely with product and business teams to translate business problems into data science solutions or data analytics research.
• Define clear success metrics and KPIs.
• Turn insights into actionable recommendations that impact revenue and player behavior.
• Ensure all models and analyses align with real business outcomes, not just technical performance.
• Design, build, and deploy ML models (e.g., churn prediction, LTV forecasting, revenue uplift, player segmentation) from experimentation to production.
• Define and implement standardized, scalable DS/DA processes across the team: model development lifecycle (design → validation → production).
• Code quality, documentation, and reproducibility.
• Experimentation and evaluation frameworks.
• Continuously improve delivery efficiency, reducing time from idea → production.
• Identify opportunities to automate manual analytical workflows using AI/ML.

Skills

SQL

Python

ML

Statistics

Experiment design

A/B testing

KPIs analysis

Predictive modeling

Churn modeling

LTV forecasting

Retention analytics

User behavior modeling

BigQuery

Spark

Hive

Git

Tableau

Looker

Power BI

Causal inference

Education

Bachelor’s or Master’s degree in Statistics, Mathematics, Computer Science, Economics, or a related quantitative field

Tools

BigQuery

Spark

Hive

Git

Tableau

Looker

Power BI

Job description

We are toogeza, a Ukrainian recruiting company that is focused on hiring talents and building teams for tech startups worldwide. People make a difference in the big game, we may help to find the right ones.

Currently, we are looking for a Lead Data Scientist for SpinLab.

Location: Remote

Job Type: Full-Time

About our client:

Spinlab helps slot gaming leaders unlock the potential of their data, enhancing business outcomes and strengthening their competitive edge in the market. The company collects and processes data using advanced methods and technologies to provide clients with clear, actionable recommendations based on real metrics. SpinLab’s goal is not just to collect data but to help businesses use it for maximum efficiency and amplify their performance results.

Role Overview:

As a Lead Data Scientist, you will combine hands-on expertise, technical leadership, and product thinking to drive the development of scalable ML solutions.

You will play a key role in:

• Ensuring what we build drives business value

• Defining how we build (processes, standards, scalability, performance)

Responsibilities:

• Work closely with product and business teams to:

  • Translate business problems into data science solutions or data analytics researches

  • Define clear success metrics and KPIs

  • Turn insights into actionable recommendations that impact revenue and player behavior

  • Ensure all models and analyses are aligned with real business outcomes, not just technical performance

  • Design, build, and deploy ML models (e.g., churn prediction, LTV forecasting, revenue uplift, player segmentation) from experimentation to production.

• Define and implement standardized, scalable DS/DA processes across the team:

• Model development lifecycle (design → validation → production)

• Code quality, documentation, and reproducibility

• Experimentation and evaluation frameworks

• Continuously improve delivery efficiency, reducing time from idea → production

• Identify opportunities to automate manual analytical workflows using AI/ML

Requirements:

• Bachelor’s or Master’s degree in Statistics, Mathematics, Computer Science,Economics, or a related quantitative field.

• 5+ years of experience as a Senior Data Scientist role/Lead role, leading both analytical and data science domain work.

• Strong SQL and Python skills; experience with large datasets, notebooks, reproducible analysis, and Git-based workflows.

• Solid knowledge of ML, statistics, experimental design, A/B testing, holdout evaluation, and business KPI analysis.

• Commercial experience with predictive modeling, classification, segmentation,forecasting, model evaluation, and business impact measurement.

• Experience with churn, uplift, LTV, retention, campaign analytics, or user behaviormodeling is a strong advantage.

• Strong analytical and problem-solving mindset; ability to find the story in the data:uncovering trends and explaining them in clear business terms.

• Commercial Experience working with large datasets and distributed computing tools(BigQuery, Spark, Hive, or similar).

• Solid understanding of experimental design and statistical testing (A/B testing,hypothesis testing, confidence intervals).

• Familiarity with causal inference techniques (e.g., Propensity Score Matching, Instrumental Variables, Difference-in-Differences, uplift modeling), and predictivemodeling techniques.

• English B2+

Will be a plus:

• Experience in gaming, gambling, fintech, e-commerce, subscription, or other user-behavior-driven products.

• Experience with BI tools such as Tableau, Looker, or Power BI.

• Product mindset: the ability to go beyond numbers and propose actionable solutionsthat make an impact.

Benefits:

• Work on meaningful data products and shape them with your vision.

• 25 vacation days + 15 sick days + 1 birthday leave.

• Budget for English classes.

• Budget for health insurance.

• Annual education & development budget.

• Remote-friendly culture with a small, dedicated team.