Senior Data Scientist

Warsaw/Wroclaw, Poland
Sofia, Bulgaria
Budapest, Hungary

Pivotics is an AI software design and implementation company with the headquarters based in Las Vegas (Nevada) and its R&D offices located in Poland, Ecuador and Belarus.

Role Description:

We are on the lookout for a Senior Data Scientist to join our team and tackle the critical challenge of analyzing firmware failure log files to identify and address bugs causing system failures.

The successful candidate will play a pivotal role in improving the reliability and performance of SSD products by employing advanced data analysis techniques to extract meaningful insights from diverse and semistructured log data for one of the biggest world-known manufacturing vendor.

  • Log Analysis: Analyze semistructured log files generated during firmware failure testing to identify patterns, anomalies, and potential sources of failure. Extract relevant information from different types of logs, such as performance data, time series, screenshots, and more.
  • Feature Extraction: Develop and apply robust feature extraction techniques to distill essential information from complex log data. Transform raw logs into structured data representations suitable for analysis.
  • Cohort and Causal Analysis: Conduct cohort analysis to group similar failures together and identify commonalities. Perform causal analysis to understand the underlying factors contributing to failures and identify potential bugs.
  • Graph Analysis: Utilize graph analysis techniques to uncover relationships and dependencies within the firmware ecosystem. Model interactions between different modules, addresses, and system components to pinpoint failure triggers.
  • Time Series Analysis: Apply time series analysis methods to logs containing temporal data. Identify trends, patterns, and anomalies over time to uncover hidden failure patterns.
  • Collaboration: Collaborate with cross-functional teams, including firmware engineers and customer engineering teams, to understand the firmware development process, gather domain knowledge, and validate findings.
  • Communication: Effectively communicate findings and insights to both technical and non-technical stakeholders. Present complex technical information in a clear and concise manner.
  • Continuous Improvement: Stay up-to-date with the latest advancements in data analysis, machine learning, and firmware development. Identify opportunities to enhance analysis methodologies and contribute to the improvement of the overall failure analysis process.
  • Education: Bachelor's degree in Computer Science, Engineering, Statistics, or a related field. Advanced degree (Master's or PhD) is preferred.
  • Experience: A minimum of 2-3 years of hands-on experience in firmware development is required to understand the nuances of the subject field. Additionally, candidates should possess 2-3 years of practical experience in data analysis, including feature extraction, cohort analysis, causal analysis, and time series analysis.
  • Data Analysis Skills: Strong proficiency in data analysis methods, statistical techniques, and feature extraction from diverse and semistructured data sources.
  • Domain Knowledge: In-depth understanding of firmware development processes and challenges. Familiarity with firmware log formats, failure modes, and debugging practices.
  • Technical Skills: Proficiency in programming languages commonly used in data analysis (Python, R, etc.). Experience with data manipulation, analysis, and visualization libraries (e.g., pandas, NumPy, matplotlib, etc.).
  • Communication: Excellent communication and interpersonal skills. Ability to collaborate with cross-functional teams, explain complex technical concepts to non-technical stakeholders, and present findings effectively.
  • Graph Analysis: Familiarity with graph analysis techniques and tools to model relationships and dependencies within firmware systems.
  • Time Series Analysis: Experience with time series analysis methods to uncover patterns and anomalies in temporal data.
  • Customer Interaction: Experience in communicating with customer engineering teams, understanding customer requirements, and addressing customer concerns is a strong plus.
  • Problem-Solving: Strong analytical and problem-solving skills. Ability to think critically and creatively to identify root causes of failures.
  • Continuous Learning: Demonstrated commitment to staying updated with the latest advancements in data analysis methodologies and firmware development practices.
  • Team Player: Ability to work collaboratively in a fast-paced, dynamic team environment.
Preferred Qualifications:
  • Advanced Degree: Master's or PhD in a relevant field, with a focus on data analysis, machine learning, or a related area.
  • Previous Firmware Failure Analysis: Previous experience in analyzing firmware failure data to identify bugs and performance issues.
  • Machine Learning: Familiarity with machine learning techniques and their applications in failure analysis.
  • Project Leadership: Experience leading data analysis projects, including managing timelines, resources, and deliverables.
Contract terms:

Work schedule: flexible and remote work schedule
Contracts: B2B
Terms: Full-time employment / ability to work from any EU location

Benefits & perks:
  • Friendly and united international team of colleagues
  • Hybrid/ remote working model
  • Flexible time schedule
  • Knowledge sharing, training and self-development opportunities
  • 14 days of paid vacation according to B2B contract
  • Assistance with relocation if needed
  • Corporate events' celebrations, outdoor activities, pizza Fridays, bar days

If you feel that you are a great fit, please submit your CV.

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