Eli India - Data Scientist

The Data Scientist will support, customer operational, financial & risk management teams with actionable solutions analyzing company data. The ideal candidate is adept at using large data sets to find opportunities & using models to test the effectiveness of different courses of action.

They must have:

- Strong experience using a variety of data mining, analysis methods, data tools and building & implementing models.

- Extensive experience creating and using algorithms & running simulations.

- Proven ability to drive business results with their data-based insights.

Responsibilities :

- Build & leverage predictive models & machine learning algorithms to increase & optimize customer experiences, profitability, operational effectiveness, reduce risk other business outcomes.

- Work with stakeholders throughout the organization to identify opportunities for leveraging company data to drive

business solutions.

- Customer Churn models.

- Advanced financial and sales forecasting.

- Dynamic pricing and price elasticity.

-Supply chain optimization modeling.

- Customer behavioral modeling.

- Text modeling.

- Mine & analyze data from company databases to drive optimization & improvement across the full spectrum of the enterprise.

- Analyze processes & systems to extract insights from structured & unstructured data.

- Develop processes & tools to monitor & analyze model performance & data accuracy.

- Assess the effectiveness & accuracy of new data sources & data gathering techniques.

- Develop company A/B testing framework & test model quality.

- Processing, cleansing, & verifying the integrity of data used for analysis.

- Doing ad-hoc analysis & presenting results in a clear manner.

- Manage analytics database, noting anomaly detection & running diagnostics.

- Training business operators on the uses and optimization of advanced algorithms.

Qualifications :

- Bachelor's degree in Statistics, Mathematics, Computer Science, Engineering, Data Science or another quantitative field, Master's degree preferred;

- 5-7 years of experience manipulating data sets & building machine learning and advanced statistical models:

- Experience using statistical and programming languages (R, Python, C/C++, Perl, Java SPSS, SLQ, etc.) to manipulate

data & draw insights from large data sets;

- Excellent understanding of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, GLM/Regression, Random Forest, Boosting, text mining, social network analysis, etc.) & their real-

world advantages/drawbacks.

- Knowledge of advanced statistical techniques & concepts (regression, properties of distributions, statistical tests & proper usage, etc.

- Experience using web services: Redshift, S3, Spark, DigitalOcean, etc;

- Experience analyzing data from 3rd party providers: Google Analytics, Site Catalyst, Core metrics, Ad words,Crimson Hexagon, Facebook Insights, etc.

- Experience visualizing/presenting data for stakeholders using Qlik, Domo, D3, Tableau, etc.

- Experience with data modeling, dimensional modeling & working with large structured & unstructured data sets;

- Experience with ETL tools assessing data quality & developing remediation plans;

- Knowledge & experience in Master Data Management & Data Governance Implementations;

- Experience in agile software methodologies in BI, Data Integration & Data Analytics projects.

- Financial Services & Mortgage industry experience is a big plus.