Andersen is hiring a Staff Data Scientist Machine Learning Engineer for a project developing an AIpowered advertising platform to predict customer lifetime value and optimize campaign performance.

The customer is a technology company that develops software solutions to help businesses improve operational efficiency and make datadriven decisions.

The project is focused on developing and enhancing an AIpowered advertising optimization platform that predicts customer lifetime value using machine learning models.

Responsibilities

Building and maintaining predictive Lifetime Value pLTV models using XGBoost, CatBoost, and BG NBD within a tiered scoring architecture, routing users into appropriate model tiers based on data availability and observability rather than applying a onesizefitsall regression approach.

Designing, implementing, and maintaining model calibration layers to transform raw predictions into platformready values, incorporating haircut scalars, linear, logarithmic, and rankbased normalization, and asymmetric loss functions that penalize overestimating lowvalue customers more heavily than underestimating highvalue customers.

Owning feature engineering processes in BigQuery, developing and maintaining Goldlayer feature tables from cleaned Silverlayer data, including RFM metrics, behavioral embeddings, category affinity, and purchase velocity.

Ensuring feature quality and reliability by evaluating data completeness, monitoring missingvalue rates, and excluding features with high missing rates among new users rather than relying on imputation.

Monitoring model drift and distribution shifts, implementing residual logging, comparing pre and postsignal deployment cohorts, and identifying causal contamination in retraining datasets resulting from the models influence on user acquisition.

Maintaining and improving batch UnionFind identity resolution algorithms in BigQuery, connecting GA4 behavioral identifiers with Shopify transactional identifiers and optimizing identity match rates to improve signal quality.





Developing and maintaining productiongrade Python applications running on Google Cloud Run Jobs, orchestrating workflows through Apache Airflow, and ensuring reliable delivery of MLgenerated signals to advertising platforms.

Implementing and maintaining automated testing, CI CD pipelines, idempotent processing, and dryrun safety mechanisms to ensure production stability, prevent costly errors, and protect client advertising performance.

Musthaves

Handson experience in Machine Learning Engineering using Python, including developing, deploying, and maintaining productiongrade ML models, for 5 years.

Proven experience with gradient boosting algorithms XGBoost, CatBoost, or LightGBM, including hyperparameter tuning, feature importance analysis, and advanced model evaluation.

Strong proficiency in SQL and BigQuery, including complex feature engineering queries, scheduled data transformations, and data validation.

Handson experience deploying and maintaining ML workloads on Google Cloud Platform GCP, including Cloud Run, Airflow Composer, Vertex AI, and Pub Sub.

Solid understanding of model calibration, businessoriented loss functions, and the impact of prediction errors on downstream optimization systems.

Practical experience integrating ML model outputs with external systems through APIs, such as advertising platforms, recommendation engines, pricing systems, or bidding systems. Strongly preferred

Experience in ecommerce or DirecttoConsumer DTC environments, particularly customer lifetime value LTV prediction, purchase forecasting, churn modeling, or customer segmentation.

Familiarity with probabilistic customer models BG NBD, GammaGamma, or similar frameworks or strong foundations in Bayesian statistics.





Experience with advertising platform integrations, including Google Ads API ConversionUploadService, Enhanced Conversions, Meta Conversions API CAPI, or similar serverside event tracking systems.

Knowledge of identity resolution and entity matching techniques, including graphbased identity stitching, probabilistic matching, or crossdevice identity resolution.

Level of English from UpperIntermediate and above.

Reasons why this job would be interesting to you

Andersen cooperates with such businesses as Samsung, Reuter Gruppe, TSystems, TUI, Ryanair, Johnson Johnson, etc. This project is just your beginning here working with us means reliability and prospects.

We have been strengthening our expertise since 2007. During this time, we have formed an excellent BA SA team with streamlined processes, which now consists of more than 200 qualified analysts.

We welcome specialists from every part of the world.

We give our employees an opportunity to attend and participate in the companys BA meetups, as well as offer a compensation program for international professional certificates.

There are many different ways to grow and develop at our company. You can improve as a tech specialist or a resource manager, and all your activities will be decently rewarded.

You will have an opportunity to take on the role of a mentor and help a group of BA SA beginners grow.

Our employees have access to Andersen Knowledge Base, where they can take courses in a variety of areas the art of negotiation, PreSale Discovery, Agile essentials, product ownership, microservice architecture, API design, SQL, AWS, GDPR, UX UI, people management, and more.

Bolsa de trabajo México ofrecemos puesto de Staff Data Scientist Machine Learning Engineer para el sector de Informatica Telecomunicaciones en la empresa Andersen Lab de Cuauhtémoc. Salario acorde a tu experiencia y al salario medio del sector. Actualiza ahora tu currículum vitae y postúlate a este empleo. Tipo de empleo Jornada completa.

📌 Staff Data Scientist Machine Learning Engineer (Cuauhtémoc)
🏢 Andersen Lab
📍 Cuauhtémoc