Lead Data Scientist

Montevideo - Uruguay

Monthly Salary: Not Disclosed

Posted on: 3 days ago

Vacancies: 1 Vacancy

Job Summary

Design and build production-ready data pipelines using SQL to support financial analytics and forecasting.
Aggregate balances and transactions across multiple core systems and data sources.
Ingest historical and projected cash flow drivers including fundraising investments realizations fees taxes and credit facilities.
Develop and maintain financial and cash flow projection models in Python.
Translate existing Excel-based models and business logic into automated scalable data science workflows.
Build historical cash flow bridges to explain liquidity movements and reconcile results with administrator records.
Enable forward-looking projections and scenario analysis through user-driven assumptions such as deployment pace leverage constraints and cash minimums.
Collaborate with stakeholders to understand the meaning of financial data and transform raw data into reliable analytical models.
Ensure data validation reconciliation auditability and robustness across all pipelines and models.

Qualifications :

Strong experience with SQL and building data pipelines in production environments (mandatory).
Proficiency in Python for data analysis modeling and automation.
Experience translating complex business logic into scalable analytics solutions.
Ability to quickly learn and work with complex financial datasets.
Familiarity with Microsoft Excel.
Experience with dbt and Snowflake is a plus.
Basic knowledge of financial concepts is required; a stronger background in Finance or Accounting is considered a plus.
Strong communication skills and ability to work with cross-functional stakeholders.
Leadership capabilities and autonomy to operate effectively in a remote environment.

What about languages

Advanced English proficiency is required for effective communication with international teams and stakeholders.

How much experience must I have

5 years of experience in Data Science Analytics or a related field.

Additional Information :

Our perks and benefits:

Every day lunches! (headquarters):

Vegetarian vegan gluten and sugar free options.
Gourmet meals every Friday with our on-site chef!

Flexible working options to help you strike the right balance.

All the equipment you need to harness your talent (Macbook and accessories).

Snacks and beverages available everyday (headquarters).

After office events football tennis and game nights (headquarters).

Everyone is welcome to join our football league every Wednesdays and Fridays.

Challenge your teammates to a pool game and win the offices trophy! Tennis courts available for friendly matches.

Not a sports person Dont worry we also have chess championships game and music nights for you to join!

Learning opportunities:

AWS Certifications (we are AWS Partners).
Study plans courses and other certifications.
English Lessons.
Learn from your teammates on our Tech Tuesdays!

Mentoring and Development opportunities to shape your career path.

Anniversary and birthday gifts.

Great location and even greater teammates!

So what are the next steps

Our team is eager to learn about you! Send us your resume or LinkedIn profile below and well explore working together!

Remote Work :

Yes

Employment Type :

Full-time

Design and build production-ready data pipelines using SQL to support financial analytics and forecasting.Aggregate balances and transactions across multiple core systems and data sources.Ingest historical and projected cash flow drivers including fundraising investments realizations fees taxes and ...

Design and build production-ready data pipelines using SQL to support financial analytics and forecasting.
Aggregate balances and transactions across multiple core systems and data sources.
Ingest historical and projected cash flow drivers including fundraising investments realizations fees taxes and credit facilities.
Develop and maintain financial and cash flow projection models in Python.
Translate existing Excel-based models and business logic into automated scalable data science workflows.
Build historical cash flow bridges to explain liquidity movements and reconcile results with administrator records.
Enable forward-looking projections and scenario analysis through user-driven assumptions such as deployment pace leverage constraints and cash minimums.
Collaborate with stakeholders to understand the meaning of financial data and transform raw data into reliable analytical models.
Ensure data validation reconciliation auditability and robustness across all pipelines and models.