It's fun to work in a company where people truly BELIEVE in what they are doing!
We're committed to bringing passion and customer focus to the business.
Data Analytics with 4+ Years of Data Science experience and more important with Machine learning and SAS (mandatory).
Modeler should have background in the new languages Python and hopefully PySpark would be preferred.
Background in cluster analysis and logistic regression.
Excellent communication skills / Good presentation skills.
Master degree in Statistics / Maths / Economics with good and consistent academic record.
Insurance industry experience a plus, but not required
History of consistently delivering business results in a timely fashion
Ability to work effectively in dynamic, rapidly changing, team-based environment.
Must balance high-priority, long-term projects with short-term, immediate deadlines.
Solid creative thinking and problem solving skills.
Lead Data Analytics / Data Scientist
Predictive Modelling / Strategic Analysis
Key Responsibilities & Accountabilities
Employ and interpret appropriate data analysis techniques and statistical methodologies such as regression analysis (both linear and non-
linear), cluster analysis, CHAID, factor analysis / principal component analysis, time series, survival models, experimental designs using SAS and other statistical software independently
QA / QC data and analysis output to ensure accuracy
Provide quality, statistically valid analysis and related output
Take a proactive role in analysis design and execution
Appropriately account for the timeliness and quality of all assignments
Collaborate with cross-functional internal resources
Monitor project progress relative to timeline and scope
Present statistical results to both technical and non-technical audience in a clear manner
Knowledge / Experience / Technical Skills
Master degree in Statistics with good and consistent academic record
4 to 8 years’ experience preferred; fresher from top tier institutes with some data science exposure will be considered.
Expert level programming skills in Python, SAS, SQL, and R with machine learning concepts.
Beginner to intermediate skills on data visualizations tools as Tableau, Qlikview is desirable.
Solid Grounding in Statistics or any Quant Discipline Strong Data Management skills (ability to handle large data sets)
Must possess strong oral and written Communication and Presentation / Story-boarding skills
Proficiency in MS Office; including PowerPoint, Word, Excel and Outlook
Strong analytic thought process and ability to interpret findings
Proficiency with various statistical methodologies such as regression analysis (both linear and non-linear), cluster analysis, CHAID, factor analysis / principal component analysis, time series, survival models, experimental designs using SAS and other statistical software
Behaviours / Competencies
Able to think Big Picture
Prioritize the deliverables based on the importance
Demonstrate Can do’ competency in the projects
Qualified applicants will be considered without regard to race, color, age, disability, sex (including pregnancy), childbirth or related medical conditions including but not limited to lactation, sexual orientation, gender identity or expression, veteran or military status, religion, national origin, ancestry, marital or familial status, genetic information, status with regard to public assistance, citizenship status or any other characteristic protected by applicable equal employment opportunity laws.