Bachelor’s degree or higher in Computer Science, Data Science, Engineering, Mathematics, Applied Statistics, or related field.

Experience 3+ years with machine learning in industry environment.

Experience 5+ years coding in Python, Scala, or similar.

Advanced understanding of probability, statistics, machine learning, data science.

Expertise in data correlation/feature analysis, analysis of machine learning models, and optimizing models for accuracy.

Proficiency in transforming and cleaning data & working across multiple models.

Ability to research and manipulate complex and large data sets (both distributed and non-distributed).

Strong fundamentals in problem solving, algorithm design, and model building.

Ability to solve complex business problem through logical and creative thinking.

Strong ability to synthesize complex information.

Excellent Code writing capability in Python  and familiarity with relevant ML packages.

Familiarity with libraries such as Pandas, Scikit-learn etc.

Experience of working on Fraud detection solution.

Excellent knowledge of anomalies/outliers detection using unsupervised algorithms – clustering, Local Outlier Factor, Isolation Forest , etc.

Deep learning experience would be added advantage.

Experience with Spark DataBricks frameworks.

Interest in applying data science in the fields of compliance.

Strong written and verbal communication skills.