Data Scientist - Fraud Analytics

Adelik Business Solutions

Role : Data Scientist with Fraud domain

Notice period : Not more than 60 days.

Requirements
• Graduate level degree preferred with concentration in a quantitative discipline such as statistics, mathematics, economics, operations research, computer science or aligned discipline
• 3-5 years practical experience working as a data scientist applying machine learning to real-world problems
• Communication skills to articulate technical aspect of model development to internal and external customers
• Excellent understanding of machine learning techniques and algorithms, such as Classification, Regression, Clustering, Feature Engineering, Decision Trees, KNN, Gradient Boosting, etc.
• Experience with common data science toolkits such as R, Python, Anaconda, TensorFlow, SQL, Scikit-learn, etc.
• Proficiency in using query languages such as SQL
• Familiarity with applied statistical concepts such as distributions, statistical testing, regression, regulation
• Logical, evidence-based problem solving and critical thinking skills
• Team focused attitude and evidence of supporting project team members

Job Description

The Data Scientist will help us improve our modeling processes and develop highly accurate, explainable and replicable modeling solutions for our clients. The primary focus will be in applying machine learning, predictive analysis, data mining techniques, and in building and training high quality models.

Specific tasks may include mining transaction descriptions, optimizing/automating our modeling pipeline using AWS based infrastructure from data gathering/manipulation, leveraging existing/new machine learning techniques and creating model documentation.

The Position Will Entail
• Utilizing statistical and machine learning techniques to create high performing models that comply with regulatory and privacy requirements and address business objectives and client needs
• Researching and developing new approaches, keeping ones skills up to date
• Testing new methods of statistical analysis, software, and data sources for continual improvement of quantitative solutions, implementing as needed
• Processing, cleansing, and verifying the integrity of data used for analysis
• Performing ad-hoc analysis and presenting results clearly
• Communicating results and ideas to key decision makers
• Creating clear and easy to understand documentation for models
• Presenting analysis, progress reports and results to internal and external customers
• Collaborating with a Team Lead to develop technical/business approaches and new or enhanced technical tools
• Participating in collaboration for implementation
• Completing all responsibilities as outlined on annual Performance Plan
• Completing all special projects and other duties as assigned
• Must be proficient in Fraud risk domain and building up the models.
• Must have experience in Large data sets.