What You’ll Do:

• Predict future business outcomes of our portfolio companies by applying data mining techniques (both supervised & unsupervised learning)
• Connect & blend data from various data sources unlocking hidden patterns & trends within enterprise organizations (python, pandas, or SQL)
• Clean & structure data to eliminate redundant or unneeded information to facilitate reliable & robust analysis
• Choose analytical tools (segmentation, predictive models, personalization) based upon specific business problems across variety of industries (retail, industrial, manufacturing, telecom)
• Build predictive models that are conceptual & logical that support data-driven insights for deployment on modern data platforms (spark, Hadoop & other map-reduce tools).
• Partner with data engineers by proving requirements gathered during data discovery to ensure the right metrics (data model, architecture and infrastructure) are put in place when building data pipelines
• Develop containerized algos that are productionalized & deployed in hybrid cloud environments (GCP, Azure)

Who You Are:

• Quantitative minded and have:
• Knowledge of quantitative methods such as linear algebra, predictive analytics and machine learning algorithms
• Experienced in analyzing and exploring large datasets with Python, Pandas, SQL.
• You are an engineer and have experience in:
• ETL process
• Data warehousing and data architecture concepts
• Data validation and quality assessment processes
• Model implementation
• Ability to break down technical ideas and present them in business-friendly language
• Bachelors, Masters or PhD in statistics, math, physics, computer science, information systems or other quantitative disciplines.
• It is preferred to have experience working with one of the major cloud solutions (AWS, GCP and Azure) but not required.