Role and Responsibilities:

• Perform exploratory and targeted data analyses using descriptive statistics and other methods


• Running end-end data sciences projects from a conceptualization to completion


• Building modeling frameworks to estimate churn propensity, cross sell and upsell opportunities


• Clearly articulate and present recommendations to business partners, and influence future plans based on insights


• Continuously discover, evaluate, and implement new technologies to maximize development efficiency


• Ability to develop and deploy scalable and reproducible analytical models for answering variety of business problems


• Identifying opportunities for improvement across our industry solutions

Basic Qualifications:

You will have Bachelor or Master’s degree in Statistics, Mathematics, Computer Science or a related field and 6 years' experience in an analytics/DS related field with exposure to SaaS business data

What are the key characteristics that would make you an ideal candidate:

High proficiency in data mining, modeling, validation and insight generation

Excellent working knowledge of statistics, mathematics, machine learning, data mining, deep learning!

Strong programming skills in Python, fluency in data manipulation (SQL, Spark, Pandas), machine learning (e.g., scikit-learn, Keras/TensorFlow, pymc3) and optimization (e.g., linear programming) tools

Able to prepare data pipelines and feature engineering pipelines to build robust models using SQL, PySpark, Azure Data Studio etc.

Experience with NLP libraries like Spacy, Genism, Glove, doc2vec etc.

Exposure to real-world MLOps is a plus

Experience in cloud computing platforms and large-scale databases (preferably in Azure) is a plus

Drive and willingness to go the extra mile with a strong work ethic