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Data Scientist

Mid / Senior
New

14.000 – 18.000 RON Net

Bucharest Hybrid

About the Client

Our client is an innovative software company focused on transforming complex, high-volume data into clear, actionable insights. Its platform empowers organizations to make informed decisions through real-time analytics, forecasting, and operational intelligence.

The company develops cloud-native solutions for large-scale data processing, streaming, analytics, and decision support, handling over one billion data updates per day from over 1000+ data sources daily.

The Role

Responsibilities

  • Develop and enhance Python-based libraries, data pipelines, and workflows for data extraction, feature creation, and supervised learning applications. 
  • Monitor and support daily forecasting operations, including runtime oversight, issue resolution, and model configuration management. 
  • Partner with engineering teams to facilitate the successful deployment of research models into production systems. 
  • Analyze data trends and operational behavior to identify root causes and resolve moderately complex challenges independently. 
  • Design scalable forecasting and machine learning solutions while considering their impact on business users and market participants. 
  • Contribute to research and development initiatives focused on improving forecast quality and model performance. 
  • Present technical processes, results, and performance indicators clearly to stakeholders and collaborative teams. 
  • Maintain comprehensive documentation of model approaches, operational procedures, and system workflows to support reliability and knowledge sharing.

Must-haves

  • Master's degree in Statistics, Mathematics, Data Science, Computer Science, or a related quantitative discipline. 
  • At least 3 years of professional experience in data science with a focus on forecasting, predictive analytics, or machine learning models. 
  • Advanced proficiency in Python and SQL for data processing, analysis, and model development. 
  • Hands-on experience with machine learning frameworks and production-level data pipeline development. 
  • Ability to work effectively in an operational environment, managing real-time model performance, troubleshooting issues, and ensuring forecasting system reliability.

Nice-to-haves

  • Prior experience in energy markets, power systems, or grid infrastructure.
  • Background in econometrics, statistics, or quantitative forecasting techniques.

Benefits

  • Performance bonus of 10% to 15% of annual base salary
  • Flexible time-off policy with untracked vacation days

Selection Process

Interview Process & How to Prepare

  1. Screening Interview (with Hiring Manager) Focus: culture fit, background, and your motivation. Be ready to walk through your CV and ask questions about the company.
  2. Panel Interview (mixed US/RO panel, evening slot 17:00-18:00 start, ~2 hours)
  • Hour 1: Behavioral round covering conflict resolution and ownership of responsibilities. Prepare concrete examples from your own experience (STAR format works well).
  • Hour 2: Technical round. You'll receive a dataset 2 days before the interview and be asked to build a forecast from it. In the interview, you'll walk the panel through your approach and justify your modelling choices.

Good to Know

Come with real examples, not hypotheticals. For the technical round, be ready to explain your reasoning, not just your results: why you chose that model, how you handled missing data or outliers, and what trade-offs you made.

Victor Cosman

Victor Cosman

Talent Sourcer

Interested in this role? Reach out and let's talk.

Connect on LinkedIn → Email victor.cosman@edurom.ro →

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