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Data Scientist-1

Bucharest

Pay
Pay not listed
Work setting
Not stated
Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
Apply at Diconium

What you’ll work on

Full posting
  • Build and evolve causal ML solutions for pricing, especially price elasticity with DML

  • Recalibrate models across markets and brands, comparing results with previous runs

  • Turn client business questions into well-identified ML/AI solutions with end-to-end ownership

  • Extract information from large, imperfect data sources and detect data-quality problems

  • Evaluate and iteratively improve model performance and efficiency

From the employer’s posting
Build and evolve causal ML solutions for pricing, in particular price elasticity estimation with Double Machine Learning (DML).
Own periodic model recalibrations across markets and brands: rerun pipelines on new data windows, compare results against previous runs, and explain results.
take end-to-end ownership of analyses, translating business questions from our clients into well-identified ML/AI solutions.
Extract valuable information from large, heterogeneous and often imperfect data sources, and detect data-quality problems.
Evaluate model performance and iteratively improve accuracy and efficiency.
Education & alternatives
Must have skills: - Bachelor's degree or higher in Computer Science, Statistics, Mathematics, Physics, Economics/Econometrics, or a related quantitative field. - At least 4 years of relevant work experience.

Tools in this posting

  • Python
  • AWS
  • Databricks
  • Docker
  • MLflow
  • Power BI
  • S3
  • SageMaker
  • Spark
  • Tableau
  • NumPy
  • pandas
  • Polars
  • scikit-learn
  • Streamlit
  • XGBoost
Source — Tool mentions in context
- Communicate findings and insights effectively to both technical and non-technical stakeholders. - Contribute to a production-grade, config-driven Python codebase using modern engineering practices (testing, typing, code review, spec-driven development, AI-assisted coding). Must have skills:
- Proven experience in machine learning and AI, with a focus on practical applications. - Strong proficiency in Python and the scientific stack (pandas and/or polars, NumPy, scikit-learn, statsmodels, gradient boosting such as XGBoost), writing clean, tested, maintainable code (pytest, type hints, linting). - Strong understanding of statistical methods and concepts.
- Excellent communication skills with the ability to present complex technical concepts clearly. - Hands-on experience with cloud ML platforms, ideally AWS (SageMaker, S3), and experiment tracking (e.g. MLflow). - Fluent English
- Experience with model monitoring, recalibration and data/concept drift analysis. - Experience with data processing in Spark and Databricks. - Experience with data visualization, dashboarding tools or simple frontends for visualization (Streamlit, Dash, Tableau, PowerBI).
- Experience deploying ML/AI models into production environments. - Familiarity with Git-based workflows, Poetry, pre-commit, CI, containerization (Docker), and AI coding assistants / spec-driven development. - Ability to write clear technical reports (Markdown, LaTeX).
- Experience with data processing in Spark and Databricks. - Experience with data visualization, dashboarding tools or simple frontends for visualization (Streamlit, Dash, Tableau, PowerBI). - Experience deploying ML/AI models into production environments.

Posting record

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Actively hiringFirst seen by us 3 days ago, still listed, and not a repost of an earlier posting.

Status in our records
Live
First seen by us
Oct 28, 2026 · 3 days ago
Recorded sightings
5
Last seen by us
Oct 31, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

Your next step

  • Have your resume and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.
  • Ask the employer about the pay range before committing time to the process.

Complete your application on diconium.wd3.myworkdayjobs.com. The employer’s form will show what is required.

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Job description

View original posting ↗

Join our global team of experts 


At Diconium, you will work on projects that connect software, data, AI, and human expertise to create digital products, services, and operating models that deliver measurable business impact. Together with 2,500 experts across our international teams, you will help build, run, and scale intelligence across the full value chain.

In everything we do, we prioritize people and genuine human connections, ensuring a supportive and inclusive work environment. Our hybrid workplace also provides a high degree of flexibility.

Role / Tasks

  • Build and evolve causal ML solutions for pricing, in particular price elasticity estimation with Double Machine Learning (DML).
  • Collaborate with cross-functional teams (data engineering, pricing experts, client stakeholders) and take end-to-end ownership of analyses, translating business questions from our clients into well-identified ML/AI solutions.
  • Own periodic model recalibrations across markets and brands: rerun pipelines on new data windows, compare results against previous runs, and explain results.
  • Extract valuable information from large, heterogeneous and often imperfect data sources, and detect data-quality problems.
  • Evaluate model performance and iteratively improve accuracy and efficiency.
  • Communicate findings and insights effectively to both technical and non-technical stakeholders.
  • Contribute to a production-grade, config-driven Python codebase using modern engineering practices (testing, typing, code review, spec-driven development, AI-assisted coding).

Must have skills:

  • Bachelor's degree or higher in Computer Science, Statistics, Mathematics, Physics, Economics/Econometrics, or a related quantitative field.
  • At least 4 years of relevant work experience.
  • Proven experience in machine learning and AI, with a focus on practical applications.
  • Strong proficiency in Python and the scientific stack (pandas and/or polars, NumPy, scikit-learn, statsmodels, gradient boosting such as XGBoost), writing clean, tested, maintainable code (pytest, type hints, linting).
  • Strong understanding of statistical methods and concepts.
  • Experience with time-series and panel data, including seasonality, outliers and structural breaks.
  • A rigorous, hypothesis-driven approach to analysis: forming and testing hypotheses with reproducible scripts and reporting negative or inconclusive results honestly.
  • Ability to work independently and collaboratively in a fast-paced environment.
  • Excellent communication skills with the ability to present complex technical concepts clearly.
  • Hands-on experience with cloud ML platforms, ideally AWS (SageMaker, S3), and experiment tracking (e.g. MLflow).
  • Fluent English

Nice to have:

  • Domain knowledge in pricing, revenue management, or the automotive industry (list vs. transaction prices, discounts and incentives, financing/leasing, model lifecycles).
  • Experience with price elasticity / demand modelling or causal ML libraries (e.g. EconML, DoubleML).
  • Experience with model interpretability (SHAP), hyperparameter optimization (Optuna) and data validation (pandera, Pydantic).
  • Experience with model monitoring, recalibration and data/concept drift analysis.
  • Experience with data processing in Spark and Databricks.
  • Experience with data visualization, dashboarding tools or simple frontends for visualization (Streamlit, Dash, Tableau, PowerBI).
  • Experience deploying ML/AI models into production environments.
  • Familiarity with Git-based workflows, Poetry, pre-commit, CI, containerization (Docker), and AI coding assistants / spec-driven development.
  • Ability to write clear technical reports (Markdown, LaTeX).
  • Previous experience in the consulting/service industry.

WHAT WE HAVE TO OFFER


Discover new skills and improve your strengths, adapt your working day to your personal lifestyle, celebrate community, sustainability and diversity. And sweeten your working life with awesome perks and benefits!

Professional & Personal Growth: Develop yourself both professionally and personally through training programs, free language courses, competence centers and an active tech community.

Flexible Work-Life Balance: Benefit from hybrid work, workation, flexible hours, parental support and sabbaticals.

Embrace Diversity & Sustainability: Engage in our Sustainability Hub, diverse communities, Diversity Taskforce and after-work activities.

Comprehensive Benefits: Enjoy public transport tickets, job bikes, access to exclusive Volkswagen employee conditions when leasing or purchasing a vehicle, health offers, supplementary insurances, a pension plan and various discounts.


WHAT WE VALUE


At Diconium, we value and recognize the unique perspectives and experiences of each individual. With this in mind, we welcome and cherish every single application equally. At the same time, we stand up against any type of discrimination and harassment based on gender, age, skin color, religion, sexual orientation, origin, disability, gender identity and other protected characteristics.
 

If you have any questions, feel free to reach out.

Your contact person is

Elena, elena.filip@diconium.com
Source details

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Location & working pattern

Bucharest

At Diconium, you will work on projects that connect software, data, AI, and human expertise to create digital products, services, and operating models that deliver measurable business impact. Together with 2,500 experts across our international teams, you will help build, run, and scale intelligence across the full value chain. In everything we do, we prioritize people and genuine human connections, ensuring a supportive and inclusive work environment. Our hybrid workplace also provides a high degree of flexibility. Role / Tasks
More source context
Professional & Personal Growth: Develop yourself both professionally and personally through training programs, free language courses, competence centers and an active tech community. Flexible Work-Life Balance: Benefit from hybrid work, workation, flexible hours, parental support and sabbaticals. Embrace Diversity & Sustainability: Engage in our Sustainability Hub, diverse communities, Diversity Taskforce and after-work activities.
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