My path to being a Technical Recruiter started when I was a Sales Rep selling Telecom services back in 1996. One of my calls was to a small recruiting firm in Foster City, which ended up recruiting me and my life has been recruiting focused since.
While the mechanics of a job search are very basic, its the intricate details that can muddle things up. That's where my experience comes in. One thing I will never do is to send your resume to a client without finding out if you are interested in the opportunity.
I am also a firm believer that if I treat my candidates and clients with respect and professionalism, they will be relationships for life. This is important, as the key to being a successful recruiter is the ability to have candidates feel comfortable about giving their friends as referrals.
Using complex algorithms to mine the vast untapped data sources every company has and then applying predictive analytics that allows our customers to increase their rate of return for sales enablement in the enterprise market. The goal is to increase repeat and recurring revenue on a large scale. With their product, aftermarket sales teams have actionable and timely insights into customers’ needs and can close more sales in less time.
Looking for Data Scientist with lead/management experience to help us transform data into amazing products.
Our Aftermarket Engagement Platform aggregates and enriches customer data, analyzes customer history and behavior using sophisticated machine learning and statistical analysis, and surfaces actionable customer insights to drive aftermarket revenue growth.
Developing machine learning software and statistical data models that can generalize across customers, but can automatically adapt to each of their individual features.
Brainstorm data product ideas with product management and data science teams and mentor junior team-members. Work with fellow engineers to build out parts of the infrastructure, effectively communicating your needs and understanding theirs.
Meet with external customers and understanding their businesses and their challenges.
Build intelligence into backend services to make them run smarter.
Proven knowledge with applied statistics and probability/ predictability data outputs.
Keep up to date with cutting-edge machine learning/ big data methods and techniques.
Experience presenting insights to executives and non-technical audiences around product analytics data.
You are passionate about automating everything and applying scientific methods to solve business and engineering requirements.
Shift quickly from deep thinking to implementing in production
Can thrive in team environments; using agile methodology and interacting with Product Leaders, Scientists and Engineers to solve technology's greatest challenges.
Learn quickly in a fast-paced, dynamic team environment.
Industry experience with writing code (e.g. SQL, Python, R) and taking ML models/ algorithms to production.
Preference for 5+ years of industry experience (without PhD); at least 2-3+ years of industry experience with PhD.
Completed a Bachelor's and/or Master's degree related to Computer Science, Statistics or related major studying AI (artificial intelligence), ML (machine learning), Data Science or Mathematics .