The Engineering organization at Earnix is charged with developing state-of-the-art analytical and AI/ML models, solutions & algorithms that are embedded into the Earnix suite of cloud services. We continuously promote analytical and algorithmic innovation that addresses a wider set of business problems & challenges faced by financial Institutions. We are seeking an?experienced, innovative & business-savvy Analytics professional to join us and help us build the next big analytical thing. You will lead a team of data scientists and engineers, build and grow the Earnix Labs program, and have an impact on the Earnix products.
Position Intro:
Earnix is a leading provider of advanced pricing and rating solutions tailored for the insurance and banking industry. Our software empowers actuaries and data scientists within financial companies to make data-driven decisions and optimize pricing strategies. With a commitment to innovation and a deep understanding of the market, Earnix is at the forefront of revolutionizing how financial companies approach pricing and rating.
Requirements:
You’ll do it using:? Advanced degree (MA/MS.C. or higher) in Computer Science/ Data Science/Statistics/ Engineering/ Economics or any related quantitative field with a focus on data analysis, applied statistics, machine learning/ deep learning At least 8 years of practical experience as a researcher with significant business experience At least 5?years of experience managing highly qualified Data Scientists/Analytics professionals Expertise in a wide range of machine learning/statistical/data analysis and state-of-the-art algorithms & applications Experience in working with external data sources, real-time data & processing big data covering both structured and unstructured data Practical experience in addressing real-world business problems. (e.g., pricing, product personalization, event detection, etc.) Experience building end-to-end analytical solutions in financial services or other relevant industries (e.g., retail, web marketing, cyber, etc.) Proficiency in Python and Scala Strong technical and technological background with good familiarity with a wide range of ML /AI & Big data tools/solutions/platforms with a particular interest in open-source solutions/tools (e.g., AWS Sagemaker, MLOps tools, etc.) Sufficient mathematical background for reading applied academic papers Strong verbal & written English communication skills You’ll excel by: Leadership & managerial skills:?the ability to start and lead projects, development of people, collaboration with other departments Creative and innovative mind:?Fast learner & self-motivated Thinking outside of the box while supporting key business and customer-facing functions within the organization Track record of successful innovation and its implementation in a managed cloud service Experience with AWS cloud services – an advantage General FinOps, Insurance and/or banking industry experience – an advantage You’ll do it using:? Advanced degree (MA/MS.C. or higher) in Computer Science/ Data Science/Statistics/ Engineering/ Economics or any related quantitative field with a focus on data analysis, applied statistics, machine learning/ deep learning At least 8 years of practical experience as a researcher with significant business experience At least 5?years of experience managing highly qualified Data Scientists/Analytics professionals Expertise in a wide range of machine learning/statistical/data analysis and state-of-the-art algorithms & applications Experience in working with external data sources, real-time data & processing big data covering both structured and unstructured data Practical experience in addressing real-world business problems. (e.g., pricing, product personalization, event detection, etc.) Experience building end-to-end analytical solutions in financial services or other relevant industries (e.g., retail, web marke
You’ll do it using:? Advanced degree (MA/MS.C. or higher) in Computer Science/ Data Science/Statistics/ Engineering/ Economics or any related quantitative field with a focus on data analysis, applied statistics, machine learning/ deep learning At least 8 years of practical experience as a researcher with significant business experience At least 5?years of experience managing highly qualified Data Scientists/Analytics professionals Expertise in a wide range of machine learning/statistical/data analysis and state-of-the-art algorithms & applications Experience in working with external data sources, real-time data & processing big data covering both structured and unstructured data Practical experience in addressing real-world business problems. (e.g., pricing, product personalization, event detection, etc.) Experience building end-to-end analytical solutions in financial services or other relevant industries (e.g., retail, web marketing, cyber, etc.) Proficiency in Python and Scala Strong technical and technological background with good familiarity with a wide range of ML /AI & Big data tools/solutions/platforms with a particular interest in open-source solutions/tools (e.g., AWS Sagemaker, MLOps tools, etc.) Sufficient mathematical background for reading applied academic papers Strong verbal & written English communication skills You’ll excel by: Leadership & managerial skills:?the ability to start and lead projects, development of people, collaboration with other departments Creative and innovative mind:?Fast learner & self-motivated Thinking outside of the box while supporting key business and customer-facing functions within the organization Track record of successful innovation and its implementation in a managed cloud service Experience with AWS cloud services – an advantage General FinOps, Insurance and/or banking industry experience – an advantage You’ll do it using:? Advanced degree (MA/MS.C. or higher) in Computer Science/ Data Science/Statistics/ Engineering/ Economics or any related quantitative field with a focus on data analysis, applied statistics, machine learning/ deep learning At least 8 years of practical experience as a researcher with significant business experience At least 5?years of experience managing highly qualified Data Scientists/Analytics professionals Expertise in a wide range of machine learning/statistical/data analysis and state-of-the-art algorithms & applications Experience in working with external data sources, real-time data & processing big data covering both structured and unstructured data Practical experience in addressing real-world business problems. (e.g., pricing, product personalization, event detection, etc.) Experience building end-to-end analytical solutions in financial services or other relevant industries (e.g., retail, web marke
This position is open to all candidates.
