Seedz is a Brazilian technology start-up in the booming agriculture sector. We are a fintech at heart, digitalizing agro through loyalty-focused campaigns.
We partner with industries who produce tractors, seeds, fertilizer and pesticide and with their re-sellers’, creating sales incentives and loyalty program for farmers. Our purpose is to innovate and create efficiency in the most important sector of the world economy.
Data at Seedz
Here at Seedz, data is not a support area. We are very proud to be a strategic team, a team of leaders and specialists in our field. We are here to work, develop and grow together.
We are happy to be building an environment where high performance does not depend on micromanagement, but on freedom and flexibility.
Responsabilidades e atribuições
As the Senior Data Scientist at Seedz, you’ll own and structure the DS product roadmap.
You will lead discovery sessions with our partners to understand the needs of the future and create MVPs.
You’ll provide direction to the Data Science capability as a whole and challenge how we grow.
You’ll be a partner with business stakeholders and the wider data team to add measurable value to Seedz.
Partner closely with business stakeholders to structure roadmaps of DS solutions;
Own and develop strategic DS solutions for our business areas;
Lead a small team of data science specialists developing the components embedded in our products;
Proactively identify and champion DS projects that solve complex problems across multiple domains;
Apply specialized skills and fundamental DS methods to inform improvements to our business.
Requisitos e qualificações
What we’re looking for
4+ years of experience in a data science role solving high impact business problems;
Experience delivering business impact through analysis and data products using DS;
Expertise solving complex and highly impactful quantitative business problems with at least one scripting language (Python, R, etc.) and SQL;
Domain expertise in statistical inference / experimentation;
Experience with statistical methods such as regression, or experiment design and analysis, building productionized machine learning systems or other advanced techniques;
Experience in building data pipelines and ETL;
Experience with data visualization using Power BI or similar data visualization tools;
Proven knowledge in working with AWS, S3, Big Data and integrating data from various Web Sources;
Results orientated, curious, attention to detail, and a strong collaborator;
Excellent strategic and analytical thinking skills.
The ideal candidate
Chooses simplicity over complexity;
Gets bored of repetitive tasks;
Is sceptical and constructive;
Sees data science as a means not an end;
Values creating a legacy.
- Remote work;
- Flexible hours;
- 40 work hours per week.