Regular Data Scientist

✅ The offer is addressed to individuals working in Poland ✅

Project Description:

We are looking for a Data Scientist to drive data-driven decision-making and evaluate the real-world impact of deployed systems. As a key member of our small but impactful team, you will work at the intersection of data analytics, machine learning, and business strategy to provide actionable insights. This role offers a unique opportunity to collaborate with transit agencies, product teams, finance, engineering, and company leadership to solve complex problems and unlock new opportunities using data.

Responsibilities:

- Design and implement data pipelines and ETL processes to enable efficient and reliable data access for analytics and decision-making.

- Develop and maintain dashboards and reports to track key performance indicators (KPIs) and provide actionable insights to stakeholders.

- Set up monitoring and alerting systems to detect anomalies and ensure data quality and system reliability.

- Conduct deep-dive analyses to support day-to-day decision-making across teams, leveraging both structured and unstructured data.

- Collaborate with engineering teams to ensure seamless integration of data pipelines and analytics tools into operational workflows.

- Perform exploratory data analysis (EDA) to uncover trends, anomalies, and insights that inform business strategies and operational decisions.

- Act as a data advocate by clearly communicating findings and recommendations to both technical and non-technical stakeholders.

- Contribute to the development of scalable data science workflows and best practices within the organization.

Mandatory Skills Description:

- Master's or PhD in Data Science, Statistics, Computer Science, Transportation Engineering, Economics, or a related field.

- 3+ years of experience in data science, machine learning, or a related field, with a track record of delivering impactful data solutions.

- Proficiency in Python and experience with data science libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch.

- Strong experience with SQL and working knowledge of data warehouse systems such as Amazon Redshift, Google BigQuery, or Snowflake.

- Expertise in statistical analysis, machine learning algorithms, and model evaluation techniques.

- Familiarity with data pipeline tools and frameworks such as Airflow, DBT, or similar.

- Experience working with visualization tools like Tableau or Looker to translate insights into actionable recommendations.

- Excellent problem-solving skills with the ability to analyze complex data and provide clear, data-driven insights.

- Strong communication skills with the ability to present findings to both technical and business audiences.

Nice-to-Have Skills Description:

- Experience working with cloud platforms, especially AWS, and deploying models using cloud-based services.

- Familiarity with geospatial analytics and processing spatial datasets.

- Experience working with large-scale time-series and mobility datasets (e.g., GTFS, GPS traces, transit logs).

- Prior experience in a startup environment and a desire to make a significant impact.

Languages:

English: B2 Upper Intermediate