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Senior Data Science Engineer

1 month ago
Bulgaria, Germany, Poland, Portugal, Romania, Spain
Full-time
Senior
Data Scientist
Data Science and Analytics
AWS LightGBM MLflow MLOps NLP NumPy OpenSearch Pandas Python PyTorch Scikit-learn TensorFlow XGBoost
Apply Now
Trinetix

Trinetix

Trinetix provides comprehensive software product engineering and design services to Fortune 500 companies and emerging brands, enabling them to innovate and enhance their digital operations for sustainable growth in a competitive landscape.

Internet Software & Services
251-1K
Founded 2011
View All Jobs 2

Description

  • Design, develop, and productionize demand forecasting models (e.g., XGBoost, BSTS, Temporal Fusion Transformer) with hierarchical reconciliation across 545+ locations.
  • Develop cascading optimization solutions using MILP and min-cost flow solvers (PuLP, OR-Tools, Gurobi) and evolve hybrid ML+optimization pipelines.
  • Implement document intelligence pipelines including Amazon Textract + LayoutLMv3 and Retrieval-Augmented Generation (RAG) workflows for contract intelligence and semantic reasoning.
  • Deploy and operate models on AWS SageMaker using training jobs, endpoints, Model Monitor, Feature Store, and Pipelines to ensure scalable, reliable production systems.
  • Implement explainability and model-interpretation tooling (SHAP, LIME, Captum) and integrate champion/challenger, A/B testing, and model/data drift detection.
  • Build and operationalize survival and out-of-spec prediction models (Kaplan–Meier, Cox Proportional Hazards, XGBoost-Survival) and monitor their business impact.
  • Collaborate closely with engineering and business stakeholders to translate requirements into ML solutions and drive measurable outcomes.
  • Own the end-to-end ML lifecycle from experimentation and model development to scalable production deployment and ongoing maintenance.

Requirements

  • Proficient in Python and core ML libraries: PyTorch or TensorFlow, scikit-learn, XGBoost or LightGBM, pandas, and NumPy.
  • Experience with time series and forecasting methods such as BSTS, Prophet, Temporal Fusion Transformer (TFT), and hierarchical forecasting with MinT reconciliation.
  • Experience with optimization techniques including Linear Programming, MILP (PuLP, OR-Tools), constraint satisfaction, and min-cost flow optimization; familiarity with Gurobi is a plus.
  • Practical experience deploying and operating ML on AWS SageMaker (Training Jobs, Endpoints, Model Monitor, Clarify, Feature Store, Pipelines).
  • Familiarity with explainability and MLOps tools: SHAP, LIME, Captum, MLflow, A/B testing, champion/challenger frameworks, and model/data drift detection.
  • Experience building document intelligence or NLP pipelines; familiarity with Amazon Textract, LayoutLMv3, RAG pipelines, Amazon Bedrock, or OpenSearch vector databases is a plus.
  • Knowledge of advanced ML methods such as Graph Neural Networks (GNNs), Deep Reinforcement Learning, survival analysis (Cox, XGBoost-Survival), and attention-based models is desirable.
  • Proven ability to operationalize models at enterprise scale and collaborate with cross-functional engineering and business teams to deliver business impact.
  • Strong focus on model explainability, reliability, and production readiness.

Benefits

  • Continuous learning and career growth opportunities.
  • Professional training and English/Spanish language classes.
  • Comprehensive medical insurance.
  • Mental health support.
  • Specialized benefits program with compensation for fitness activities, hobbies, pet care, and more.
  • Flexible working hours.
  • Inclusive and supportive company culture.

Interested in this position?

Apply directly on the company website

Apply Now

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