ETRM Data Scientist (all genders)

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We are looking for candidates with advanced expertise in time-series forecasting, predictive modeling, and deep learning, complemented by hands-on experience in scalable MLOps frameworks. A master’s degree in mathematics, statistics, or data science is required, with a preference for candidates holding a Ph.D. Proficiency in Azure Machine Learning, Databricks, PySpark, and optimizing performance of operational machine learning models is essential. Ideal candidates will have a proven ability to optimize models, automate workflows, and drive innovation while delivering efficient, scalable solutions in forecasting projects.

Job description:
Job Description

We are looking for candidates with advanced expertise in time-series forecasting, predictive modeling, and deep learning, complemented by hands-on experience in scalable MLOps frameworks. A master’s degree in mathematics, statistics, or data science is required, with a preference for candidates holding a Ph.D. Proficiency in Azure Machine Learning, Databricks, PySpark, and optimizing performance of operational machine learning models is essential. Ideal candidates will have a proven ability to optimize models, automate workflows, and drive innovation while delivering efficient, scalable solutions in forecasting projects.

Key Responsibilities

• Develop and implement reusable and scalable machine learning systems for time-series forecasting.
• Analyze, retrain, and fine-tune machine learning models based on evolving data trends and business requirements to ensure long-term efficiency and reliability.
• Automate machine learning workflows, including deployment, monitoring, and retraining, using Azure Machine Learning as an MLOps technology.
• Utilize PySpark for efficient data processing and analytics in large-scale environments.
• Collaborate on data engineering tasks in Azure Databricks and implement scalable storage solutions using Azure Data Lake.

Mandatory skills

• Master’s degree in mathematics, Statistics, Data Science, or related fields is mandatory
• A Ph.D. in Mathematics, Statistics, Data Science, or similar areas is preferred but not mandatory
• Data Science:
  • Extensive experience in time-series forecasting, predictive modelling, and deep learning
  • Proficient in designing reusable and scalable machine learning systems
  • Proficiency in statistical and machine learning approaches for time-series analysis, including ARIMA, LSTM, Prophet, Linear Regression, and Random Forest
  • Strong command of machine learning libraries, including scikit-learn, XGBoost, Darts, TensorFlow, and PyTorch, along with data manipulation tools like Pandas and NumPy
  • Proventrack record of analysing and optimizing performance of operational machine learning models to ensure long-term efficiency and reliability
  • Expertise in retraining and fine-tuning models based on evolving data trends and business requirements
  • Proven expertise in designing and implementing explicit ensemble techniques such as stacking, boosting and bagging to improve model accuracy and robustness
• MLOps Implementation:
  • Proficiency in leveraging Python-based MLOps frameworks for automating machine learning pipelines, including model deployment, monitoring, and periodic retraining
  • Advanced experience in using the Azure Machine Learning Python SDK to design and implement parallel model training workflows, incorporating distributed computing, parallel job execution, and efficient handling of large-scale datasets in managed cloud environments
• PySpark Proficiency
  • Strong experience in PySpark for scalable data processing and analytics
• Azure Expertise:
  • Azure Machine Learning: Managing parallel model training, deployment, and operationalization using the Python SDK
  • Azure Databricks: Collaborating on data engineering and analytics tasks using PySpark/Python
  • Azure Data Lake: Implementing scalable storage and processing solutions for large datasets

B͏enefits

• New Hires Buddy-Program
• Regular All-hands Meetings
• Referral Program
• Comprehensive Learning Offerings
• Company pension plan
• Highly international, high-Performance culture
• Diversity is in our DNA
• Women network

Seniority level

• Seniority level

  Entry level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Engineering and Information Technology

• Industries

  IT Services and IT Consulting

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