Senior Data Scientist, Finance

Key Skills

Amazon RedShift, Data science techniques, Finance, Google BigQuery, Machine learning techniques, Python Programming, Snowflake, SQL

Job Description

We’re growing and looking for a talented Senior Data Scientist to come aboard and join our Data Science team in Finance. Our team develops, operationalizes, and maintains the ML-based forecasting models for some of Snowflake’s core financial metrics. Our work product informs many facets of corporate planning and is heavily used by teams inside and outside of Finance, as well as by executive management, the board, and in external reporting to our investors. Our team also works closely with Product to assess the financial impacts of new product features, with Sales to understand and predict customer behavior, and develops and applies anomaly detection algorithms to cost and revenue data.

We are looking for someone who has significant experience employing ML algorithms on time series data and is both equally at home conducting applied research as well as implementing and operationalizing their ideas to meet business driven timelines. As Finance touches on all aspects of the business, you should have a desire to learn about customer behavior and the important drivers of various departments.

AS A SENIOR DATA SCIENTIST IN FINANCE AT SNOWFLAKE, YOU WILL :

• Work with time-series datasets to refine and extend the core forecasting models and algorithms we use for many of our key financial metrics
• Develop and refine ML models that are critical to Snowflake’s business
• Identify and build solutions for operational use cases in forecasting —e.g. further automation, system monitoring and alerting, outlier detection, etc.
• Generate insights into drivers of our business leveraging statistical methods and participate in extending and developing internal tools used for this purpose
• Think creatively to find optimal solutions to our complex, typically unstructured problems.

OUR PREFERRED CANDIDATE WILL HAVE :

• MS/PhD in a quantitative discipline (Math, Statistics, Operations Research, Economics, Engineering, or CS)
• Extensive experience building production-ready ML models for time series applications
• Experience conducting open-ended research projects and literature reviews
• 5-7+ years of experience with Python and familiarity with SQL
• Experience working with large-scale machine-generated data (e.g., log, application, or customer-usage data).
• Hands-on experience with MPP databases, such as Snowflake, Redshift, BigQuery, Vertica, etc.
• Ability to clearly present learnings to business leaders and technical stakeholders.
• The ability to thrive in a dynamic environment. That means being flexible and willing to jump in and do whatever it takes to be successful.

Every Snowflake employee is expected to follow the company’s confidentiality and security standards for handling sensitive data. Snowflake employees must abide by the company’s data security plan as an essential part of their duties. It is every employee's duty to keep customer information secure and confidential.

The following represents the expected range of compensation for this role:

• The estimated base salary range for this role is $148,000 - $218,500.
• Additionally, this role is eligible to participate in Snowflake’s bonus and equity plan.

The successful candidate’s starting salary will be determined based on permissible, non-discriminatory factors such as skills, experience, and geographic location. This role is also eligible for a competitive benefits package that includes: medical, dental, vision, life, and disability insurance; 401(k) retirement plan; flexible spending & health savings account; at least 12 paid holidays; paid time off; parental leave; employee assistance program; and other company benefits.

Snowflake is growing fast, and we’re scaling our team to help enable and accelerate our growth. We are looking for people who share our values, challenge ordinary thinking, and push the pace of innovation while building a future for themselves and Snowflake.