Data Scientist

As we expand into this region, we are looking for a Data Scientist to join Piaxo team. The role is for our client from United States, which is involved in battery development area. In this role, you will develop intelligent algorithms and data-driven solutions that leverage real-time vehicle and manufacturing data. You will work at the intersection of machine learning, embedded systems, and manufacturing excellence, turning raw data into actionable insights that enhance product quality, reliability, and customer experience.

About Piaxo

Piaxo is an engineering company delivering end-to-end R&D services for the automotive industry, covering the complete V-Cycle from concept to validation. We stand out through senior engineering teams, a strong focus on quality and processes, and proven delivery against key milestones such as ASPICE compliance, supported by TISAX Level 3 certification and our role as an official Tehnica Engineering reseller.

Headquartered in Romania, with offices in Cluj-Napoca and Timișoara and an international presence in Munich, Germany, Piaxo is expanding its Timișoara site into a permanent office with an automotive laboratory. The location is planned to scale to 120+ engineers and technical experts, delivering complete product development across all competencies in line with ASPICE 4.0, as part of a long-term, well-defined program developed with a major Tier-1 customer, offering stability, technical depth, and long-term career continuity.

Responsibilities:

Key Responsibilities

• Build data analysis pipelines to understand vehicle signals related to energy consumption and component performance across different vehicle applications.
• Build, develop, validate, and maintain predictive models that assess the health and performance of connected powertrain or energy systems.
• Build data analysis pipelines to understand machine signals related to product manufacturing and assembly processes.
• Build, develop, validate, and maintain optimization models to improve production throughput, reduce scrap rates, and enhance overall product quality.
• Collaborate closely with other data scientists, engineers, and business stakeholders to craft solutions.
• Communicate details of the data-driven decision process to non-technical stakeholders.
• Provide ML and statistical support to other areas of the organization to enable data-informed decision-making across teams.

Required Qualifications

• Bachelor’s Degree in Statistics, Mathematics, Computer Science, or a related engineering field.
• 3+ years of professional experience in data science, machine learning, or a related field (or equivalent academic experience through a Master’s or Ph.D. program).
• Strong programming skills in Python, Julia, or R, and ML/statistical packages such as Scikit-learn, SciPy, Statsmodels, PyTorch, Keras.
• Proficiency in data visualization tools such as Power BI or Tableau.
• Solid understanding of probability, statistics (e.g., hypothesis testing, experimental design, power analysis, mixed-effect models), linear algebra, and the mathematical foundations of machine learning.
• Deep knowledge of machine learning techniques for supervised and unsupervised learning, including feature selection, dimensionality reduction, regression, classification clustering, and time series analysis.
• Experience working with databases and writing SQL queries.
• Proven experience in developing, training, validating, and deploying machine learning or statistical models into production environments.
• Experience using data visualization techniques for data analysis and model explanation.
• Experience effectively collaborating with non-technical stakeholders.
• Self-driven, curious, and creative mindset with the ability to work effectively in cross-functional teams within a dynamic and fast-paced environment.

Preferred Qualifications

• Experience and understanding of various deep learning architectures and their application to different problem.
• Hands-on experience with big data technologies such as Databricks, Spark, Snowpark, etc.
• Experience working with cloud platforms including Microsoft Azure, AWS.
• Proven experience deploying machine learning solutions to production environments (e.g., REST APIs in Azure ML, Docker, Kubernetes) as part of large-scale data science projects.
• Experience mentoring Analysts or Data Scientists.
• Familiarity with causal inference, probabilistic graphical models, Bayesian statistics, and probabilistic programming tools such as Stan, PyMC, or PyStan is a plus.
• Experience working with manufacturing, IoT, and/or battery engineering is a strong plus.
• Publications in peer-reviewed journals or conferences related to statistics, mathematics, or machine learning are considered an asset.

Opportunities for you

• Involvement in launching Piaxo’s new office in Timișoara.
• A dynamic, people-first culture with creative events.
• Work with passionate people who care about quality, collaboration, and continuous improvement.