Senior ML Engineer

Jobtailor; Deutschland; Vor Ort; EUR 70.000 - 120.000; Vollzeit

Zusammenfassung

Jobtailor in Germany is seeking an experienced data analytics/data science professional to surface actionable business insights from large datasets. You will design data models, pipelines, and ML solutions that drive KPI definition and reporting, working closely with stakeholders.

You will build and evaluate ML models, perform feature engineering, and ensure data quality and governance across the organization. Strong communication and collaboration skills are essential.

Qualifikationen

• 5+ years of experience in Data Analytics, Data Science, or a combined analytics and ML role.
• Demonstrated experience building and deploying ML models in a business context, not just academic or exploratory work.
• Strong analytical and problem-solving mindset with the ability to translate complex data into clear, actionable insight.
• Excellent communication skills to work effectively with both technical and non-technical stakeholders.
• Python proficiency for both data wrangling and ML model development: Data libraries: pandas, NumPy, matplotlib, seaborn. ML libraries: scikit-learn, XGBoost, LightGBM, or equivalent.
• Strong SQL skills including querying, optimization, and data modeling.
• Experience with dbt for building and version-controlling data transformations.
• Solid understanding of relational databases and data warehouse concepts.
• Comfort with statistical reasoning: distributions, hypothesis testing, regression, and uncertainty quantification.

Aufgaben

• Analyze large datasets to surface trends, patterns, and actionable business insights.
• Build and maintain data models, transformations, and pipelines using SQL and dbt.
• Collaborate with stakeholders to define metrics, KPIs, and reporting requirements.
• Support data governance, ensuring data quality, integrity, and accessibility across the organization.
• Document processes, workflows, and analysis outcomes for cross-functional teams.
• Design, build, and evaluate supervised and unsupervised ML models (classification, regression, clustering, forecasting).
• Lead problem framing conversations with stakeholders to translate business questions into ML-ready problem statements.
• Conduct feature engineering, selection, and transformation to prepare data for model training.
• Validate and communicate model performance using appropriate evaluation metrics (AUC, RMSE, F1, precision/recall, etc.).
• Support lightweight model deployment and monitoring, flagging performance drift and recommending retraining triggers.
• Contribute to experiment design and A/B testing frameworks where applicable.

Kenntnisse

data analysis

data modeling

SQL

dbt

machine learning

feature engineering

model evaluation

A/B testing

Python

statistical reasoning

analytical mindset

problem-solving

communication

collaboration

documentation

Tools

dbt

SQL

Jobbeschreibung

Responsibilities

• Analyze large datasets to surface trends, patterns, and actionable business insights.
• Build and maintain data models, transformations, and pipelines using SQL and dbt.
• Collaborate with stakeholders to define metrics, KPIs, and reporting requirements.
• Support data governance, ensuring data quality, integrity, and accessibility across the organization.
• Document processes, workflows, and analysis outcomes for cross-functional teams.
• Design, build, and evaluate supervised and unsupervised ML models (classification, regression, clustering, forecasting).
• Lead problem framing conversations with stakeholders to translate business questions into ML-ready problem statements.
• Conduct feature engineering, selection, and transformation to prepare data for model training.
• Validate and communicate model performance using appropriate evaluation metrics (AUC, RMSE, F1, precision/recall, etc.).
• Support lightweight model deployment and monitoring, flagging performance drift and recommending retraining triggers.
• Contribute to experiment design and A/B testing frameworks where applicable.

Requirements

• 5+ years of experience in Data Analytics, Data Science, or a combined analytics and ML role.
• Demonstrated experience building and deploying ML models in a business context, not just academic or exploratory work.
• Strong analytical and problem-solving mindset with the ability to translate complex data into clear, actionable insight.
• Excellent communication skills to work effectively with both technical and non-technical stakeholders.
• Python proficiency for both data wrangling and ML model development: Data libraries: pandas, NumPy, matplotlib, seaborn. ML libraries: scikit-learn, XGBoost, LightGBM, or equivalent.
• Strong SQL skills including querying, optimization, and data modeling.
• Experience with dbt for building and version-controlling data transformations.
• Solid understanding of relational databases and data warehouse concepts.
• Comfort with statistical reasoning: distributions, hypothesis testing, regression, and uncertainty quantification.

ATS Optimization Keywords

Hard Skills

• data analysis
• data modeling
• SQL
• dbt
• machine learning
• feature engineering
• model evaluation
• A/B testing
• Python
• statistical reasoning

Soft Skills

• analytical mindset
• problem-solving
• communication
• collaboration
• documentation