Mariana F.
Data Scientist
Hun har også praktisk erfaring med enhets- og integrasjonstesting, funksjonslagerstyring, og verktøy som Databricks, Looker og Metabase. Hennes allsidige tekniske ferdighetssett gjør at hun kan bygge pålitelige og skalerbare dataløsninger.
Mariana har en solid bakgrunn innen finans og markedsføring og har gått over til teknologibransjen, hvor hun har fire års erfaring. Hennes ekspertise spenner over analyse, kredittmodellering og anbefalingssystemer, drevet av hennes lidenskap for data og statistikk. Hun utmerker seg i å skape velutformede, datadrevne produkter som gir meningsfulle innsikter og resultater.
Med en unik kombinasjon av analytisk sans og teknisk dyktighet, er Mariana dyktig i å drive beslutninger basert på data og bygge påvirkningsrike produkter, noe som gjør henne til en ressurs for ethvert data-sentrisk team.
Hovedekspertise
Apache Spark5 år
AWS5 år
Databricks5 årErfaring6
Data Scientist
- Improved credit approvals from 20% to 50% by developing and deploying a gradient-boosting classification model.
- Increased calculation accuracy by 30% by automating the calculation of Net Present Value (NPV) from Excel to Python.
- Decreased manual analysis from 20% to 10% in offline tests by creating a fallback logistic regression model for credit approvals.
Python
SQLData Scientist
- Increased 10% email click-through rate by training, optimizing, and deploying a deep learning two-tower content-based recommendation model.
- Trained and optimized a deep learning collaborative filtering recommendation model for email campaigns.
- Responsible for planning 2023 bets, interviewing and hiring, onboarding three new hires, and documenting legacy decisions from previous owners of recommendation models at the company.
Data Scientist
- Improved credit approvals from 20% to 50% by developing and deploying a gradient-boosting classification model.
- Increased calculation accuracy by 30% by automating the calculation of Net Present Value (NPV) from Excel to Python.
- Decreased manual analysis from 20% to 10% in offline tests by creating a fallback logistic regression model for credit approvals.
PythonSQLData Analyst
- Improved accuracy in the estimation of supply availability duration by 20% by developing a Survival Analysis method, impacting Unit Economics estimation.
- Zeroed differences in numbers of the main business metrics across the company by developing a standardized metrics calculation in Metrics Governance initiatives.
- Freed 25% of work time from one analyst by translating the calculation of business targets from Excel to SQL.
- Provided reports of main business metrics for Series D and Series E investment rounds.
PythonSQL
Data Analyst
- Developed a report template and process for analysis of marketing strategies of competitors across the company.
- Developed marketing campaign results template standardized cross-company to automate performance analysis.
PythonSQL
Controller Assistant
- Calculated yearly and monthly forecast estimation for financial statements within 15% of deviation from actual values.
- Developed dashboard templates and trained teams across countries for reporting.
PythonSQLVurdering
Ingenieurskunst der Spitzenklasse
Mariana totale ytelse i en 90-minutters live teknisk vurdering rangerer i de top 25% av vurderte Data Scientist hos Proxify.
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