Kraken
Data Scientist I
Kraken, San Francisco, California, United States, 94199
Building the Future of Crypto
Our Krakenites are a world-class team with crypto conviction, united by our desire to discover and unlock the potential of crypto and blockchain technology.What makes us different?Kraken is a mission-focused company rooted in crypto values. As a Krakenite, you’ll join us on our mission to accelerate the global adoption of crypto, so that everyone can achieve financial freedom and inclusion. For over a decade, Kraken’s focus on our mission and crypto ethos has attracted many of the most talented crypto experts in the world.Before you apply, please read the
Kraken Culture
page to learn more about our internal culture, values, and mission. We also expect candidates to familiarize themselves with the Kraken app. Learn how to create a Kraken account
here .As a fully remote company, we have Krakenites in 70+ countries who speak over 50 languages. Krakenites are industry pioneers who develop premium crypto products for experienced traders, institutions, and newcomers to the space. Kraken is committed to
industry-leading security
,
crypto education
, and
world-class client support
through our products like
Kraken Pro
,
Kraken NFT
, and
Kraken Futures
.Become a Krakenite and build the future of crypto!Proof of work
Employer: Payward Operations LLC (dba Kraken)
Position: Data Scientist I
Job Location: 100 Pine Street, Suite 1250 PMB B297, San Francisco, CA 94111
The opportunity
Duties:Partner with financial fraud, product, engineering, and other relevant stakeholders to identify, prioritize, and answer the most important questions where analytics, statistical and ML modeling will have a material impact on mitigating Financial Fraud.
Drive cross functional analytic projects from beginning to end: build relationships with partner fraud teams, frame and structure questions, collect and analyze data, summarize and present key insights in support of decision making to mitigate fraud.
Work with engineers to evangelize data best practices and implement analytics solutions.
Develop, train, and deploy ML models serving predictions and automating fraud reduction processes.
Collaborate with fraud leaders, subject matter experts, and decision makers to develop success criteria and optimize new products, features, policies, and models.
Communicate key results with self-serve tools (dashboards, analytics tools) for leadership and product management.
Develop payment anomaly detection, and data modeling tools to monitor key performance indicators to improve the efficiency of payment gateways.
Design experiments for product teams to test hypotheses and help with idea generation and refinement.
Build key datasets and data pipeline automation using SQL/Python/Airflow/ETL frameworks.
Telecommuting / work from home is permitted.
Skills you should HODL
Must have experience with:Building and deploying machine learning models to detect fraudulent activities.
Advanced quantitative and data analysis, including estimation methods, time series analysis, and machine learning techniques.
Data querying languages such as SQL, scripting languages such as Python, or statistical/mathematical software such as R.
Performing in-depth research projects, examining real-world data with mathematical methods.
Cloud-computing tools and platforms such as AWS or GCP; Data visualization tools such as Tableau, Qlik, or Data Studio.
Working with large datasets, including tick data.
Identifying and implementing infrastructure improvements to minimize overall latency and maximize performance with packages such as Pandas or Pyspark.
Building databases and creating ETL pipelines for large, complex data sets with Airflow.
Minimum education and experience required:Bachelor’s degree or the equivalent in Computer Science, Data Science, Statistics or a related field.
3 years of experience in the cryptocurrency industry or related.
Employer will accept any amount of experience with the required skills.Equal Opportunity Employer
As an equal opportunity employer, we don’t tolerate discrimination or harassment of any kind. Whether that’s based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status or any other protected characteristic as outlined by federal, state or local laws.
#J-18808-Ljbffr
Our Krakenites are a world-class team with crypto conviction, united by our desire to discover and unlock the potential of crypto and blockchain technology.What makes us different?Kraken is a mission-focused company rooted in crypto values. As a Krakenite, you’ll join us on our mission to accelerate the global adoption of crypto, so that everyone can achieve financial freedom and inclusion. For over a decade, Kraken’s focus on our mission and crypto ethos has attracted many of the most talented crypto experts in the world.Before you apply, please read the
Kraken Culture
page to learn more about our internal culture, values, and mission. We also expect candidates to familiarize themselves with the Kraken app. Learn how to create a Kraken account
here .As a fully remote company, we have Krakenites in 70+ countries who speak over 50 languages. Krakenites are industry pioneers who develop premium crypto products for experienced traders, institutions, and newcomers to the space. Kraken is committed to
industry-leading security
,
crypto education
, and
world-class client support
through our products like
Kraken Pro
,
Kraken NFT
, and
Kraken Futures
.Become a Krakenite and build the future of crypto!Proof of work
Employer: Payward Operations LLC (dba Kraken)
Position: Data Scientist I
Job Location: 100 Pine Street, Suite 1250 PMB B297, San Francisco, CA 94111
The opportunity
Duties:Partner with financial fraud, product, engineering, and other relevant stakeholders to identify, prioritize, and answer the most important questions where analytics, statistical and ML modeling will have a material impact on mitigating Financial Fraud.
Drive cross functional analytic projects from beginning to end: build relationships with partner fraud teams, frame and structure questions, collect and analyze data, summarize and present key insights in support of decision making to mitigate fraud.
Work with engineers to evangelize data best practices and implement analytics solutions.
Develop, train, and deploy ML models serving predictions and automating fraud reduction processes.
Collaborate with fraud leaders, subject matter experts, and decision makers to develop success criteria and optimize new products, features, policies, and models.
Communicate key results with self-serve tools (dashboards, analytics tools) for leadership and product management.
Develop payment anomaly detection, and data modeling tools to monitor key performance indicators to improve the efficiency of payment gateways.
Design experiments for product teams to test hypotheses and help with idea generation and refinement.
Build key datasets and data pipeline automation using SQL/Python/Airflow/ETL frameworks.
Telecommuting / work from home is permitted.
Skills you should HODL
Must have experience with:Building and deploying machine learning models to detect fraudulent activities.
Advanced quantitative and data analysis, including estimation methods, time series analysis, and machine learning techniques.
Data querying languages such as SQL, scripting languages such as Python, or statistical/mathematical software such as R.
Performing in-depth research projects, examining real-world data with mathematical methods.
Cloud-computing tools and platforms such as AWS or GCP; Data visualization tools such as Tableau, Qlik, or Data Studio.
Working with large datasets, including tick data.
Identifying and implementing infrastructure improvements to minimize overall latency and maximize performance with packages such as Pandas or Pyspark.
Building databases and creating ETL pipelines for large, complex data sets with Airflow.
Minimum education and experience required:Bachelor’s degree or the equivalent in Computer Science, Data Science, Statistics or a related field.
3 years of experience in the cryptocurrency industry or related.
Employer will accept any amount of experience with the required skills.Equal Opportunity Employer
As an equal opportunity employer, we don’t tolerate discrimination or harassment of any kind. Whether that’s based on race, ethnicity, age, gender identity, citizenship, religion, sexual orientation, disability, pregnancy, veteran status or any other protected characteristic as outlined by federal, state or local laws.
#J-18808-Ljbffr