TL;DR
Senior Data Scientist (AI): Building high-impact data solutions and algorithms for global freight markets with an accent on enhancing data quality, improving ingestion pipelines, and delivering meaningful analytics. Focus on developing predictive models impacting strategic objectives and interpreting complex findings for diverse audiences.
Location: Bucharest, Romania (hybrid)
Company
hirify.global is a leading data platform transforming ocean and air freight markets by providing intelligence and market analytics.
What you will do
- Develop and deploy data solutions to solve complex business problems.
- Interpret and communicate complex findings to both technical and non-technical audiences.
- Mentor data scientists and promote best practices within the team.
- Develop predictive models that impact strategic objectives.
- Collaborate with product managers, data analysts, software engineers, and business stakeholders to design solutions.
- Contribute to a data-driven culture by sharing knowledge and expertise across the company.
Requirements
- Proven experience as a Data Scientist (2+ years for Mid-level, 4+ years for Senior-level) delivering analytical and ML solutions.
- Strong fundamentals in applied statistics, time-series analysis, and ML/AI algorithms.
- Excellent proficiency in Python or R, SQL, and NoSQL.
- Solid experience with dbt, Snowflake, and AWS services (SageMaker, S3, Glue, Athena, QuickSight).
- Working knowledge of DevOps and infrastructure tools, including Docker, Git, and Terraform.
- English: Working language, applications must be submitted in English.
Nice to have
- Advanced certifications across Snowflake, dbt, or AWS.
- Experience architecting or scaling production ML systems (e.g., feature stores, MLOps pipelines).
- Experience with Deep Learning frameworks, Spark, and Airflow.
Culture & Benefits
- Support for career growth as a specialist or into leadership/management roles.
- Transparent and open work environment empowering impact and ideas.
- Annual global company trip and opportunities for in-person meetings.
- Individual education budget and dedicated learning time during work hours.
- Emphasis on work-life balance and flexible working hours (core time 10:00-15:00).
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