Senior Data Scientist

Brasilseg

Data Scientist developing statistical and machine learning models for Brasilseg. Supporting commercial decisions and optimizing sales channels with data science techniques.

Posted 6/20/2026full-timeSão Paulo • 🇧🇷 BrazilSeniorWebsite

Tech Stack

Tools & technologies

ApacheAWSNumpyPandasPySparkPythonRayScikit-LearnSparkSQLUnity

About the role

Key responsibilities & impact

Work within the Analytics & Data Science team, developing statistical and machine learning models to support commercial decisions, optimize sales channels, and increase conversion, retention and portfolio growth with scientific rigor, controlled experimentation and large-scale production models.
Build Next Best Action models to recommend the optimal product, channel and timing — increasing cross-sell within the customer base and conversion across digital channels.
Develop churn models using behavioral and policy history to anticipate cancellation risk and trigger personalized retention actions.
Deliver propensity-to-purchase models for lead scoring and the active base, prioritizing customers by probability of purchase — guiding commercial and digital efforts.
Generate behavioral and economic segmentations to personalize communications, offers and pricing by profile.
Apply uplift modeling to measure the incremental impact of campaigns, focusing where there is a real change in behavior and reducing budget waste.
Design and analyze A/B tests and RCTs to measure the causal impact of sales, campaigns and journey changes — ensuring evidence-based decisions.
Build Marketing Mix Modeling (MMM) and multichannel attribution to measure ROI by channel and optimize budget allocation based on incrementality.
Evaluate policies without RCTs using causal methods, estimating the impact of changes such as region-based pricing.
Model predictive LTV by customer/segment to guide acquisition and retention investment and support CAC vs. LTV logic.
Build and maintain MLOps pipelines on Databricks, ensuring stability and performance of models in production.
Translate analyses into clear executive recommendations, connecting statistical metrics to business decisions.

Requirements

What you’ll need

Bachelor’s degree (Statistics, Mathematics, Engineering, Computer Science or related fields).
Advanced proficiency in Python (pandas, numpy, scikit-learn) and SQL.
Production experience with Apache Spark / PySpark / Databricks / SparkML.
Experience with AWS (S3, Glue, SageMaker, Lambda or similar) in large-scale data environments.
Strong knowledge of MLflow: tracking, model registry, champion/challenger aliases, Unity Catalog, nested runs, custom metrics and artifacts.
Experience with Databricks Feature Store (offline and online tables, Unity Catalog, point-in-time correctness, on-demand features and streaming features).
MLOps expertise: dev/test/prod lifecycle, Databricks Asset Bundles (DABs), model serving endpoints, tests (unit and integration) in notebooks, automated retraining with detection of data drift and performance degradation.
Inference in batch, real-time and streaming (including Delta Live Tables) and deployment of models to endpoints.
Ability to translate business problems into well-defined statistical / ML problems.
Previous experience in the financial, insurance or actuarial sector.
Master’s or PhD in Statistics, Econometrics, Mathematics, Actuarial Science or other quantitative fields.
Advanced knowledge in causal inference: DiD, RDD, instrumental variables (IV), propensity score; experience with observational studies and clinical/quasi-experimental trials.
Distributed training and distributed hyperparameter tuning: pandas Function APIs / UDFs, Optuna + MLflow, Ray, and awareness of vertical vs. horizontal scaling for ML workloads.
Lakehouse monitoring: drift detection, statistical tests, time series and snapshot tables, custom metrics and alerting.
Delta Live Tables and streaming pipelines; custom PyFunc models, REST API and MLflow Deployments SDK.

Benefits

Comp & perks

Health insurance
Dental insurance
Death benefit insurance
Commuter allowance (Vale Transporte)
Meal allowance
Food allowance
13th month food allowance (13ª Cesta de Alimentação)
Group life insurance
Private pension plan
Childcare and/or nanny assistance
Profit Sharing and Results (PLR)
Gympass
Day off to celebrate your birthday
Corporate University with over 500 courses
Integrated Health Program: mental, social, financial and physical wellness.

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Hard Skills & Tools

PythonSQLApache SparkPySparkDatabricksMachine LearningCausal InferenceMLOpsMarketing Mix ModelingA/B Testing

Soft Skills

Analytical ThinkingProblem SolvingCommunicationCollaborationDecision Making

Certifications

Bachelor's degreeMaster's degreePhD