We’re no strangers to emerging technology at Redfish. Today, machine learning and artificial intelligence experts are crucial talent for countless industries: financial trend forecasting, manufacturing management, health research, transportation development--and we’re just getting started. These tools give an organization the ability to bring order to a large amount of data, find a pattern in that information, and turn it into a prediction model for the future, improving both the end user experience and business outcomes.
While a plethora of industries use machine learning algorithms, many leaders don't even know what acronyms like NLP mean, much less how to leverage that technology for their business. It's hard to set job requirements that will attract the right person if you don't even know what background and type of skills to look for during the interview process. That's where Redfish staffing professionals can make an impact. We understand the data science world and can spot top talent well-versed in selecting data sets that make sense for your industry, who know how to train an algorithm, avoid overfitting and underfitting to maximize its accuracy, control for bias, and develop a comprehensive AI strategy that will deliver results.
Our team is proud to leverage the diverse creativity of the Redfish network to unlock the future. Our candidates have a passion for technology, along with expertise in statistics, data analysis, data models, and other skills crucial for success in data scientist jobs. Most importantly, we take a hands-on approach to understanding the employer's needs and preferences, using these in-depth candidate profiles as the basis of our selection process. In short, we ensure the candidate is a good fit before we send them along for an interview. As industry demands evolve at the speed of light, our dedicated ML and AI recruiters help you tackle trends and anticipate what lies ahead.
The Founder of a Bain Capital/Lightspeed Ventures startup in San Francisco needed a Lead Infrastructure engineer who combined the skills of Dev/Ops, Functional Programming, CI/CD AND Machine Learning.
They were series A and growing aggressively, so they needed someone who could do the technical work as well as lead a team underneath them. We found them a perfect M.I.T fit who has been there almost 3 yrs and helped double the size of the company!
Our engaged search process normally takes four weeks between our initial discovery call with the client and when an offer is extended. Clients get a single point of contact in our team, as well as a minimum of 20 dedicated hours each week.
The process starts with a deep dive discovery with the hiring team. This conversation focuses on two aspects: the requirements of the role and the needs and selling points of the company. Once we’ve gathered this information from the client, we use a curated four-touch candidate outreach campaign and advanced AI software to source candidates from our network. By the end of the first week, we typically have at least 5 resumes to send to clients, who get the first right of refusal on any resume sourced for their position.
Once we’ve defined the traits of the ideal candidate in our discovery call with the client, we do internal planning before going to our network. This involves separating the qualifications into “must haves” and “nice to haves”, identifying competitors that employ similar machine learning professionals, and creating a targeted four-step multi-touch campaign. We then deploy this campaign across our database and 30,000+ company followers network, leveraging our contacts as well as AI software and both paid and unpaid resources to generate qualified leads. Along the way, we provide data analysis to the client that they can use to evaluate and shape the recruiting strategy and improve the efficacy of our messaging.
We first create a list of questions that target certain skills or traits based on our discovery call with the client. As candidates are interviewed, we recalibrate with the client as necessary to make sure those questions are attracting the right candidates for their needs.
We measure our machine learning hire quality by considering factors like how many submitted candidates are interviewed, how long it took to make a placement, how long the candidate remains in the role, and feedback from clients.
We have a candidate retention rate of 86% across the industries and sectors we work with.
On average, it takes 4 weeks to fill a machine learning role.
We utilize metrics including time to hire, resumes submitted to interviews, and interview-to-hire ratio.
Working with a recruiter allows you to hire better machine learning talent more quickly, as well as saving companies the time, money, and resources they would have invested in the search. Having multiple recruiters working on a search also allows the process to be scaled, giving machine learning recruiters the capability to fill multiple roles with high-quality candidates concurrently.
The main difference comes down to the scope of the search. In a machine learning executive search, the process is more specific and targeted. More stringent criteria can mean that the search takes a bit longer, but with the result of a better long-term hire who perfectly meets the client’s needs. The payment terms are also different. With executive search, the client pays in installments throughout the process, rather than after the search is completed. Executive search firms may also charge per diems and expenses.
The network of machine learning professionals we’ve built over 30 years in the business is our biggest differentiator. Relationships are the core of this business and we always start with our network. We also have 30,000+ followers of our company that we network through.
We give them a human-focused interaction rather than a transactional one. Our goal is to build long-term relationships, and both our clients and our candidates appreciate this personal touch.
Working with a recruiter enables you to hire the best machine learning professional for the role, not just the best person in your network. The recruiting landscape has changed dramatically, and our use of AI technology, targeted messaging, and other paid and unpaid resources allows us to navigate the talent market more efficiently and at a deeper level than hiring teams can using in-house resources.
Yes, our engaged search is backed by a 60-day refund or replacement guarantee.
We start by understanding the client’s story, culture and needs through our in-depth discovery process. Next, we use this information in our screening process, and convey it to the candidates we’ve identified as a potential fit based on their skills and experience. We can also perform reference and background checks on request.
Absolutely! We want our clients and candidates to succeed, and support them throughout the hiring process. For companies, this includes helping with their job description, competitor analysis, salary ranges, and improving their interview process, as well as services like contracting, contract-to-hire, and payroll. For candidates, we help them perfect their resume and application materials and offer coaching through the interview process.
Delicately. We know the value a diverse team brings to a business and understand the crucial role recruiters play in ensuring the hiring process is free from bias. This starts by identifying areas where bias could be a factor and taking steps to ensure candidates are being fairly assessed and compared. We also observe how our clients are mitigating and preventing issues and adopt the approaches that are effective, with the goal of continuously improving the transparency, fairness, and inclusiveness of our talent sourcing and placement.
welcome feedback from clients and candidates, and feel that full disclosure and honest, transparent communication is helpful for both sides. We also serve as a conduit for feedback between clients and candidates. If an issue is sensitive, we’ll clear it with the client or candidate before starting the conversation.
Our fee is 25% of the base first-year salary of the new hire.
No. Our fee is paid in full by the client, and there is no charge for machine learning candidates to work with us.
We maintain the confidentiality of both the hiring company and the candidates throughout the process. We sign NDAs at the start of a search and get guidance from our clients on what can and can’t be shared with candidates. All information we collect from candidates and companies is securely stored and protected from unauthorized access.