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Data Scientist

1 hour, 56 minutes ago
Serbia
Full-time
Senior
Data Scientist
Data Science and Analytics
CatBoost CRM Databricks Feature Engineering GCP LightGBM Machine Learning Pandas Python Scikit-learn SQL XGBoost
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EXANTE

EXANTE

This company provides private investors and wealth managers with a comprehensive multi-currency account that grants access to over 50 global venues, enabling them to trade a diverse range of financial instruments including stocks, ETFs, bonds, futures,...

Capital Markets
View All Jobs 13

Description

  • Define and build predictive models from scratch for churn prediction, upsell/cross-sell propensity, and client lifetime value.
  • Own the full modeling lifecycle from problem framing and target definition through feature engineering, training, validation, and iteration.
  • Work with raw trading, transactional, and behavioral data from the company data warehouse.
  • Translate business concepts such as churn into measurable machine learning targets.
  • Engineer features from client activity, trading patterns, market conditions, and engagement signals.
  • Design monitoring for model performance, data drift, and model degradation over time.
  • Deliver daily client-level scores that integrate into CRM workflows and sales processes.
  • Translate model outputs into actionable insights for non-technical sales managers.
  • Collaborate with sales leadership to design interventions based on model predictions.
  • Present results, assumptions, limitations, and recommendations to senior stakeholders.

Requirements

  • 4+ years of hands-on experience building and deploying predictive models on real business problems.
  • Strong proficiency in Python, including pandas, scikit-learn, and XGBoost/LightGBM/CatBoost, plus SQL.
  • Demonstrated ability to frame ambiguous business problems as machine learning tasks independently.
  • Experience with tabular data at scale, including feature engineering, class imbalance handling, temporal validation, and avoiding data leakage.
  • Ability to communicate model results to non-technical stakeholders in plain, actionable language.
  • Experience working with time-series or event-based behavioral data.
  • Experience with churn prediction, propensity modeling, CLV, or customer scoring in any industry is a strong advantage.
  • Familiarity with survival analysis, such as Cox proportional hazards or time-to-event modeling, is a strong advantage.
  • Experience with model monitoring in production, including data drift detection, retraining pipelines, and champion-challenger frameworks, is a strong advantage.
  • Background in financial services, brokerage, or fintech is a strong advantage.
  • Experience with probabilistic CLV models such as BG/NBD, Pareto/NBD, or Gamma-Gamma is a strong advantage.
  • Familiarity with SHAP, LIME, or other model interpretability techniques is a strong advantage.
  • Experience with data warehousing tools such as BigQuery or Databricks is a strong advantage.

Interested in this position?

Apply directly on the company website

Apply Now

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