Data Science/Machine Learning Modeling Role - Python - BFSI

Looking for an Analytics professionals to analyze large amounts of raw information to find patterns that will enable to make smarter decisions to deliver even better products & solutions for customers, building data products to extract valuable business insights.

The primary focus will be in applying data mining techniques, doing statistical analysis, and building high quality prediction systems.

In this role, incumbent should be highly analytical with a knack for analysis, math and statistics. Critical thinking and problem-solving skills are essential for interpreting data with a passion for machine-learning and research, analyzing trends to make better decisions.

Basic Requirements:

- 3 - 8 years of proven experience as a Data Scientist or Data Analyst

- Understanding of machine-learning algorithms and data modeling technologies

- Cognizance of BFSI or marketing analytics landscape

- Experience of working with R, SQL and Python

- Experience of using business intelligence tools (e.g. Tableau) and data frameworks (e.g. Hadoop)

- Analytical mind and business acumen

- Strong math skills (e.g. statistics, algebra)

- Problem-solving aptitude

- Excellent communication and presentation skills

- BSc/BA/BTech in Computer Science, Engineering or relevant field; graduate degree in Data Science or other quantitative STEM streams

Preferred Requirements:

- Excellent understanding of machine learning techniques and algorithms, such as k-NN, Linear & Logistic regressions, Decision Forests, etc.

- Experience with common data science toolkits, such as R, NumPy, Pandas, scikit-learn. Excellence in at least one of these is highly desirable

- Experience of credit risk modeling and/or marketing analytics techniques

- Prior experience in building & monitoring analytics quality assurance platforms

- Experience with cloud analytics platforms (AWS, Azure, GCP) - GCP is highly desirable

- Understanding of Australian lending ecosystem from a bureau perspective is a huge plus

- Proficiency in using query languages such as SQL, Hive, Scala, Spark, Impala

- Good applied statistics skills, such as distributions, statistical testing, regression, etc.

- Data-oriented personality with keen attention to details