About HashiCorp

 HashiCorp is a fast-growing company that solves development, operations, and security challenges in infrastructure so organizations can focus on business-critical tasks. We build products to give organizations a consistent way to manage their move to cloud-based IT infrastructures for running their applications. Our products enable companies large and small to mix and match AWS, Microsoft Azure, Google Cloud, and other clouds as well as on-premises environments, easing their ability to deliver new applications for their business.

 We are looking for an experienced Data Scientist to be part of the Financial Planning & Analysis (FP&A) Digitization team.

What You Will Do

• Develop a flexible consumption revenue forecasting Machine Learning (ML) model that enables the FP&A team to forecast weekly, monthly, quarterly and annual revenue with high level of accuracy +/- 2% variance to actuals overtime. Overtime, extend the ML capabilities beyond revenue to other relevant user cases. 
• Leverage  ML to create prescriptive and predictive analytics to improve our revenue forecasting and identify opportunities for increasing revenue. 
• Apply mathematical, statistical, predictive modeling or machine-learning techniques and with sensitivity to the limitations of the techniques. Select, acquire and integrate data for analysis. Develop data hypotheses and methods,share insights and findings and continue to iterate with additional data.
• Execute high quality statistical tests/techniques to define nature and treatment of data during exploratory data analysis (EDA), selection of features and quantification of  test results.
• Develop processes, techniques, tools and documentation(design, standard operating procedures, run books, and training documents etc..) that are easily understood by other data science team members and Finance business partners responsible for forecasting revenue to analyze and monitor model performance while ensuring data accuracy.
• Execute and Implement the ML life cycle stages starting with EDA(exploratory data analysis), feature engineering, model selection criteria, training & testing approach along with robust performance monitoring and improvement of the model accuracy.
• Evaluate the business problems and assess if those could be solved using prescriptive or predictive analytics by identifying what internal or external data sources will be required. 
• Contribute to exploration and experimentation in data visualization working with the BI and Business Analyst team members working with stakeholders to determine how business leverage additional actionable insights other than predictions.
• Work closely with the IT team for deployment and changes to the ML use cases.Perform peer review for ML model codes and evaluation results for feedback and improvements.

Skills and Experience

• You demonstrate HashiCorp's principles in your daily interactions and how you approach work.
• Effective, efficient, and clear communication and collaboration skills. This role will interact with non-technical business owners.
• Proven experience developing Machine Learning forecasting models for consumption-based business cases.
• Expert knowledge of statistical algorithms  used for supervised (classification and Regression) and unsupervised learning ( clustering)
• Expert knowledge of Machine Learning based Forecasting techniques & optimizations.
• Exposure to Neural network - (LSTM), and prophet algo for forecasting would be an added advantage.
• Comfortable using structure languages like R/Python and hands-on experience using libraries like sci-kit-learn, numpy, pandas, TensorFlow, pytorch, keras, etc. to build models.
• Proven experience in integrating ML models with web applications Flask, streamlit etc.. built APIs on open source (python etc,)
• Proven experience building machine learning  usage/consumption-based revenue models- FMCG, Auto, cloud saas products
• Minimum 2 years experience and exposure to Saas Organizations.

Nice to have

• Hands-on experience in deploying models on Snowflake, AWS, or Pyspark (open source).
• Building UI for dynamic ML output in streamlit /flask app.

Education

Master’s Degree/PhD (preferably PhD) in a quantitative field (Applied Mathematics, Statistics/ Data Science) or computer science  from a Tier 1/2 institution ( IISc, IIT, NIT etc.)

AWS certified in Machine learning. 

Experience 

Overall experience of 3-5+ years working as a data scientist.

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