Job summary
Job post source
This job is directly from Earnix
Job overview
The Professional Services Consultant at Earnix supports clients in using software for data extraction, analysis, and pricing strategy development within the insurance industry, impacting client success and product effectiveness.
Responsibilities and impact
The role involves developing predictive models, utilizing machine learning and programming languages like Python and R, communicating technical results clearly, demonstrating software functionality, and training new users to ensure effective software adoption.
Experience and skills
Candidates should have extensive insurance industry analytics experience, proficiency in machine learning, Python and R programming skills, strong communication abilities, and client engagement expertise; ACAS or near-ACAS designation is preferred.
Work environment and culture
The company values honesty, candour, respect, collaboration, resourcefulness, creativity, and empathy, fostering a supportive and innovative work environment.
Company information
Earnix is a leading provider of cloud-based intelligent decisioning solutions for pricing, rating, underwriting, and product personalization, serving insurers and banks globally since 2001 with offices worldwide.
Unique job features
The role offers the opportunity to work with advanced predictive modeling and machine learning techniques in a dynamic, innovative insurance software company.
Company overview
Earnix is a global provider of advanced analytics and AI-driven software solutions for the financial services industry, specializing in pricing, product personalization, and customer analytics for banks and insurance companies. The company generates revenue by licensing its cloud-based platform to enterprise clients, enabling them to optimize pricing strategies, accelerate product innovation, and enhance customer experiences. Founded in 2001 in Israel, Earnix has expanded internationally and is recognized for integrating machine learning and real-time decisioning into core business processes. Notably, Earnix has secured significant investment rounds and partnerships, reflecting its strong market position and innovative technology. Candidates should be aware of Earnix’s reputation for fostering a collaborative, data-driven culture and its focus on digital transformation within traditional financial sectors.
How to land this job
Tailor your resume to emphasize your strong background in insurance analytics, predictive modeling, and your familiarity with ACAS or near-ACAS designation, as these are key qualifications for the Professional Services Consultant role at Earnix.
Highlight your proficiency in machine learning techniques and programming languages such as Python and R, showcasing your technical skills that align with Earnix's requirements for enhancing analytics capabilities.
Demonstrate your exceptional communication skills by detailing experiences where you translated complex technical results into clear, accessible presentations for diverse audiences, which is crucial for client engagement.
Apply through multiple platforms including Earnix's corporate careers page and LinkedIn to maximize your application visibility and ensure you don't miss any openings for this position.
Connect with current Earnix employees in the Professional Services or Analytics divisions on LinkedIn. Use ice breakers like commenting on recent Earnix innovations in insurance analytics or asking about their experience working on predictive modeling projects to initiate conversations.
Optimize your resume for ATS by incorporating keywords from the job description such as 'predictive modeling,' 'insurance analytics,' 'machine learning,' 'Python,' 'R,' 'client engagement,' and 'pricing strategies' to increase your chances of passing automated screenings.
Consider using Jennie Johnson's Power Apply feature to automate applying through multiple channels, tailor your resume with relevant keywords, and identify LinkedIn connections for networking, allowing you to focus more effectively on preparing for interviews and other job search activities.
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