PL
Antal logo
PL EN CZ SK
Enloyd logo
EN HU

Ulubione oferty

Aplikuj

New Insurance Business Unit

nr ref: /49/03/2019/DK(
Konsultant prowadzący: Dagmara Kłos (Moczarska)
Praca stała 12 marca 2019

W Antal zajmujemy się rekrutacją do ponad 20 lat. Dzięki działaniu w 10 wyspecjalizowanych dywizjach, świetnie orientujemy się w aktualnych trendach branżowych. Precyzyjnie określamy specyfikę stanowiska, klasyfikując kluczowe umiejętności i niezbędne kwalifikacje. Naszą misją jest nie tylko znalezienie kandydata, którego kompetencje wpisują się w wymagania danego ogłoszenia, ale przede wszystkim stanowiska, spełniającego oczekiwania kandydata.

Our Client is a leading data analytics provider serving customers in insurance, natural resources, and financial services. Using advanced technologies to collect and analyse billions of records, draws on unique data assets and deep domain expertise to provide first to market innovative solutions for client base. Headquartered in the US, the company operates in 27 countries, has revenues of over $2 billion and over 8000 employees in the team.

Main company's goals are delivering data, analytics, and decision support services to its customers.

We are seeking for:

Data Scientist Lead

to support high visibility, high priority, big data projects that have a significant revenue potential. Will focus on mentoring a team tasked with data cleaning, merging, and feature engineering to create model ready datasets. Will also perform some predictive modeling as an individual contributor.

You will play an integral role by transforming large highly complex data (of varying quality) into highly usable datasets. You will be tasked with leading a team who will be synthesizing creative solutions to non-trivial problems such as creating complex matching algorithms to join disparate data sources, backfilling missing data, engineering high quality features, and identifying then resolving computational inefficiencies by utilizing current generation big data techniques.

Requirements:

  • Graduate-level degree with concentration in a quantitative discipline such as statistics computer science, mathematics, economics, or operations research.
  • Strong verbal and written communications skills, listening and teamwork skills, and effective presentation skills. This is absolutely essential since you will have a lot of exposure to different internal groups (data, IT, product and sales) as well as third-party partners and customers (insurance companies).
  • Fluency in Polish and English languages.
  • Expertise in statistical modeling techniques such as linear regression, logistic regression, GLM, tree models, cluster analysis, principal components, and feature creation, validation.
  • Programming experience with SAS (STAT, macros, EM), R and other statistical software (CART, Emblem, SPSS, Matlab). Greenplum and UNIX experience is a plus. AWS experience is also a plus.

Insurance Pricing Data Lead

Prepare and lead production of deliverables for regulators and internal & external customers. Products may include loss cost reviews, filings, circulars, annual statistical filings, and customized data products to meet customer needs. Analysis will be based in actuarial science. Processes will be learned but the team will be pushed to find efficiencies and process improvements. Areas of focus are on data preparation for insurance ratemaking and analysis of said data to produce actuarially sound indications, trends, etc. Will work closely with actuaries in the US.

Requirements:

  • Graduate or Bachelor's degree with a major in Mathematics, Data Science, Statistics, Economics, Risk Management, Operational Research or related discipline.
  • At least 2 years of property- casualty insurance work experience, especially related to actuarial, data management, and analytics.
  • Data management skills or knowledge of insurance data management principles is a plus.
  • Experience in quantitative and qualitative data analysis.
  • Some familiarity with insurance coverages, actuarial methodologies and quality control.
  • Technical background should include a working knowledge of MS Office applications and understanding of computer programming concepts.
  • Knowledge of SQL, SAS, R, ETL tools or Business Rules Engines is a plus.
Aplikuj