BlackLine Careers

Description

Responsibilities:

• Bring Creativity to Data products.
• Apply machine learning methods to a variety of finance and accounting problems.
• Responsible for building and maintaining the machine learning systems, data, platform and processes.
• Build, integrate and deploy machine learning solutions into the BlackLine application in collaboration with product management, cloud, engineering and data science teams.
• Perform qualitative and quantitative data analysis.
• Cleanse and transform raw data used in machine models.
• Perform data munging, data mining, clustering & classification methods, pattern recognition.
• Comfortable with statistics, calculus and multivariate analysis.
• Participate in ML POCs, validate the results and develop production implementations.
• Build and optimize scalable machine learning solutions in the public cloud.
• Familiar with SQL, Python, R, SparkML, TensorFlow, GCP, AWS, SQL Server.
• Develop production systems in Python.
• Work independently to research and solve business and technical problems.
• Plan their work individually and as part of a team.
• Mentor and train other Data Scientists on the team.

• Strong practical experience with machine learning techniques in the industry, accounting and financial industries is a plus.
• Extensive experience solving analytical problems using quantitative approaches.
• Experience with machine learning algorithms for building ML models, their accuracy, cleanliness, reliability.
• Experience with predictive and prescriptive analyses, modeling, and segmentation.
• Have strong passion for empirical data research for practical applications.
• Ability to communicate complex quantitative analysis in clear, precise, and actionable
• Comfortable with complex, high-volume, high-dimensionality data from varying sources.
• Very comfortable with data engineering methods and pipelines.
• Expert knowledge of analysis tools such as R, Matlab, or SAS
• Experience with data warehousing, relational databases, ETL, BI, data mining.
• Experience in SQL, R, Python languages.
• Strong familiarity with GCP and AWS, SQL Server.
• Practical experience with GIT version control.
• Comfortable working with open source tools in a Unix/Linux environment.
• Experience with and ownership of data-informed decision-making.
• Experience translating business requirements into functional, and non-functional requirements.
• Strong sense of product and data ownership.
• Works independently without the need for supervision.
• Strong written and verbal skills – able to explain the work in plain language.
• MS/PhD in Computer Science or other quantitative disciplines