The company is looking to revolutionize cloud computing and AI by developing data models, predictive modeling, and data analytics and BI reporting to support financial reporting, modeling, and analysis.
Requirements
- Strong proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch) or R for modeling and analysis.
- Solid experience with SQL (Snowflake) and dbt for building and querying data models.
- Knowledge of machine learning, statistical modeling, and optimization techniques.
- Experience working with cloud platforms (AWS, GCP, Azure) and big data technologies.
- Experience with data visualization tools (Looker, Tableau, Power BI, Matplotlib, ggplot, etc).
- Experience in causal inference, econometrics, or Bayesian methods.
- Hands-on experience with ML Ops, model deployment, or data engineering workflows.
Responsibilities
- Data Modeling: Write efficient, scalable code for data analysis, model development, and automation using Python, R, SQL, dbt, or similar tools.
- Predictive Modeling: Develop, test, and implement predictive models and machine learning algorithms to solve business challenges such as revenue forecasting and churn prediction.
- Data Analytics & BI Reporting: Develop and maintain BI infrastructure in Looker to enable stakeholder analysis and reporting.
- Collaboration: Work closely with FP&A, Accounting, and other stakeholders to translate business questions into data science problems and communicate findings effectively.
- Documentation: Create and maintain detailed documentation of data architectures, processes, and best practices.
Other
- Master’s or Ph.D. in Data Science, Computer Science, Statistics, Economics, or a related field.
- 3+ years of experience in data science, analytics, or a similar role.
- Ability to work in a fast-paced, cross-functional environment.
- Flexible time off policy
- Employee Assistance Program
- Local Employee Meetups
- Reimbursement for relevant conferences, training, and education
- LinkedIn Learning's 10,000+ courses
