- 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