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Expert
MenuSteven Englander Product Mgmt, JavaScript, Blockchain, Recruiting
Chief Governance Systems Architect @ United States Lab, former Product @ CasperLabs (now Prove.AI), former Head of Product @Knowledge, Founder & CEO of RecruitingScience, former Product @[x+1] now part of Amazon, @LinkShare now Rakuten Marketing, Project/Product @RichFX now ChannelAdvisor
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24
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Areas of Expertise
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SE$2.50/min per minute(4)Product Innovation & DifferentiationSteven Englander • Greater New York City AreaCreated 10 years ago in Product & Design / Product Management20+ years of successful internet product experience across multiple industries, 4 startup employers acquired by public companies, multi-million dollar revenuesSteven Englander Greater New York City Area(4)
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SE$2.50/min per minute(4)Recruiting Top TalentSteven Englander • Greater New York City AreaCreated 10 years ago in Business / Getting Started15+ years recruiting for top internet companies, including executive management and operational positions for startups, mid-size and enterprise companiesSteven Englander Greater New York City Area(4)
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SE$2.50/min per minute(4)Online AdvertisingSteven Englander • Greater New York City AreaCreated 9 years ago in Product & Design / Product ManagementDesigned platforms in the computational advertising space, expertise in programmatic buying, DSP, RTB, retargeting, DMP, geolocation, local, predictive analytics, blockchain + crypto rewards, GDPR/CCPA and data privacySteven Englander Greater New York City Area(4)
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SE$2.50/min per minute(4)Blockchain, Web3, Smart Contracts, DeFi, DAOs, Governance, Identity, ZKPsSteven Englander • Greater New York City AreaCreated a year ago in Technology / Software Development• Identity/SSI, Certificate Authorities (CAs), Decentralized IDs (DIDs) Verifiable Credentials (VCs) and Zero-Knowledge Proofs (ZKPs) for asset, data, and relationship sovereignty • Key sharding in HD wallets, Multi-Party Computation (MPC), web3auth, multisig custodial and sovereign solutions for Web3 • Sidechains, multichain, cross-chain, IBC, CCTP, message passing, interoperability, composability, optimistic and zk-rollups, validium, zk-SNARKs, zk-STARKs, arithmetic circuits • EVM dev tools, SDKs, APIs: Truffle, Hardhat, Foundry, Infura, OpenZeppelin, web3.js, ethers.js, Ganache, Solidity, Remix, Silkworm (C++) EVM, Erigon, Moralis, thirdweb • DAOs, 3 major primitives, Snapshot, DAOstack, Aragon, Tally, Colony, DAOhaus, complex inter-DAO governance • Atomic Swaps, HTLCs, BIPs, BOLTs, Payment Channels, Commitment Transactions, Ordinal Theory, Ordinals & Inscriptions, BRC-20, Stamps, Taproot, Taro/Taproot Assets Protocol, Stacks.js, Clarity, Clarinet, Hiro, Rollkit, Rootstock, RGB, PSBTs, DLCs, splicing on Bitcoin and the Lightning Network / LND • DeFi, cryptocurrencies, price volatility, stablecoins, algorithmic, asset backed, reserve coins, reserve ratios, stablecoin peg ratios, liquidity, mint + burn fees, operating fees, participation rewards, bridges, swaps, wrapped tokensSteven Englander Greater New York City Area(4)
- Reviews 24
- Answers 5
Steve was very helpful in my research project. We covered a wide range of topics, and he's pointed me in the direction of people and resources for further investigation. I look forward to doing another call with Steve again soon.
Source: Clarity James Moran Apr 16, 2021Very useful call. Steven has been helpful and attentive to my questions, and tried to shed light on many aspects on technical hiring.
Source: Clarity Hicham Amine Jul 20, 2020Steve took his responsibilities as a Product Manager seriously at [x+1]. He was always willing to reach out across departments in order to make sure that product feature milestones had realistic time frames and that the production teams were on track to deliver releases. I enjoyed working with him and I have no hesitation to recommend his work.
Source: LinkedIn Mark Valor Mar 29, 2015I worked for Steve as a Recruiting Manager and Systems Analyst. Steve opened my mind to the world of recruiting. He helped me discover the inefficiencies in this industry and the lack of technology to truly solve the problems. Steve is hardcore - his expertise and approach in recruiting is incomparable to other recruiting agencies that I've interacted with. Through his background as a Product Manager and years of building a successful recruiting agency he has positioned his company, RecruitingScience, to use big-data to become a smarter solution for his clients.
Source: LinkedIn Julian Carlin Mar 29, 2015Steven has proven to be a fantastic partner in our recruiting efforts. On multiple occasions he was able to bring in great senior level and highly niche talent to our teams. I can always count on Steven as a critical source for recruiting the highly specialized resources needed to stay competitive in today’s market.
Source: LinkedIn Christopher Grant Mar 29, 2015Steven, was a great help in connecting me with a company and a position that was truly a great fit. He was able to make a match that has benefited all parties involved. He is detailed oriented and ensured great communication and excellent negotiations helping to make a wonderful career connection for myself.
Source: LinkedIn Ryan Gomez Mar 29, 2015Steven's value to clients goes way beyond his command of the nuances in the recruiting process. He's an experienced operator who has built businesses before and this is part of what makes him unique. He knows with great detail the skill sets that are required for excellence of execution-- and knows how to recruit hard-to-find talent to get the job done. I highly recommend Steve.
Source: LinkedIn Brad Mehl Mar 29, 2015Steve Englander is one of the most talented recruiters I know. Himself, having worked for a number of starts up. He brings deep technical knowledge and an innate ability to identifying and understanding a company's culture. Atuned to the right fit, not just from a practical perspective. He is sensitive to the emotional one as well. He is extremely intelligent and brings empathy to all candidate relationship he builds. I strongly recommend him for any given project.
Source: LinkedIn May Nguyen Aug 15, 2013After such a positive experience working with Steven, I recommend him highly as a provider of top notch recruiting and consulting services. I appreciate his straightforward, get down to business approach that ended up successfully matching me with a fantastic new opportunity at my current company. Steven's expertise, insight, clear communication throughout the prospecting/interview process and genuine concern were invaluable during a typically stressful process. Thank you so much Steven!
Source: LinkedIn Sydney Campos Aug 15, 2013Steve placed me into my current position last year. I've never worked with a recruiter who worked as hard for both sides. He kept me informed throughout the process with the straight story. I felt that he really believed in me and was an advocate for my candidacy. I highly recommend him both for job seekers looking to work with a quality recruiter and for companies looking to get "best fit" candidates.
Source: LinkedIn Matthew Sawyer Aug 15, 2013Enroll in a MOOC like Coursera, Udacity, EdX, etc. and learn something new.
I think speech systems are the future of the web. I'd look at Andrew Ng's keynote here, full video is 1+ hour: http://www.lifehacker.com.au/2015/03/the-basic-recipe-for-machine-learning-explained-in-a-single-powerpoint-slide/
I'm answering this from both a founder and a product UX design perspective. It would be helpful to have an idea as to what you're actually building to answer this question properly as many times, people think they need something when they don't necessarily need it.
You're saying you need a *top* UX designer, which would imply you're building something totally new, something where there is no known best practice for the UX of this kind of solution. Assuming that's the case, then you should be able to get a top UX designer to want to work on it based on that very challenge alone. If you explain it in this way to at least one skilled UX person, then the challenge alone should make them want to share it with their network, even if that person is not interested or unavailable or has requirements outside of what you're capable of offering.
Assuming you're not inventing something totally new, I would go onto a site like Behance or LinkedIn or Dribbble and speak with people who understand UX enough to point you in the direction of best practices for that type of solution, and then I would find perhaps a more affordable UX designer and work from there with your budget or as an equity-split/hybrid comp. If the person is not a *top* UX designer/developer, then they're likely more willing to get involved in a risk/reward scenario.
Figure out if you really need top, because that's difficult if the challenge is not there. Someone skilled can get you very far along and will be more open to working with you in an affordable way.
Get in contact with tech recruiters who are often in talks with serial tech cofounders who are looking for a new startups to join. Recruiters normally charge a fee for this, but at the early stage, you may find recruiters who will work out an arrangement with you. Placing the original tech cofounder is a sure-fire way for a recruiter to own the relationship exclusively with an early stage startup. If the recruiter believes in what you're building, perhaps they will be willing to defer payment until the company has funding or is otherwise in the position to pay fees, or work out another equity-based agreement. Ultimately, I would only select one recruiter for this type of assignment, but you can speak with several to see if they're interested. Make sure the recruiter you select is proven in exactly this type of effort... ask for a reference from another startup non-tech founder where the recruiter placed the tech cofounder.
First off, I have several people I could introduce. I'd also like to know the industry you're operating in, what the data looks like, where it comes from, and how much it needs to be cleaned up if putting into a relational database, or if the better solution would be a distributed file system like MongoDB where you don't necessarily need to normalize the data. Also, if you're a startup, or if the company is well established with many existing customers and if this is for a new initiative.
Assuming you're working with a relational database, which it sounds like you are, you will want to implement something like Tableau or build out a custom dashboard using Google Charts, HighCharts, D3Js, or any number of other potential dashboarding/visualization solutions, which usually involves some programming/scripting in JavaScript. There are paid solutions like Tableau (which is amazingly powerful), and then there are free/open source options. I'd be happy to talk about possible ways to architect the solution, and discover who you would need once I understand the variables more.
If you're building a web application, then you will likely need someone who is also a full stack developer, meaning they can handle building the back end and the front end in addition to the data requirements. Many early startups choose Ruby on Rails (because there is a ton of open source code out there for it) with Twitter Bootstrap (modified) and in order to visualize the data, they will need to work with JavaScript.
It makes sense to have this person act as initial product and to derive the insights out of the data. They're pretty much the only person who can do this anyways, because they're the ones on the data. If you're in an early stage startup, I would recommend the strongest business owner (usually the early stage startup's CEO) be directly involved with this person on communicating what value your solution brings to clients, and what they pay you for, and in brainstorming on potential features and reports. Once the solution becomes established, and many customers start using it directly, there should be a different product person interfacing to those customers over time, gathering feature requests from customers and bringing it back to the Data Scientist/Analyst who spends their time working on the data.
Depending on whether the solutions are SQL or NoSQL or hybrid, there are different types of Data Science professionals you should consider:
1. Data Scientist
2. Data Engineer
3. Data Modeler/Analyst
1. The Data Scientist handles experimenting with the data, and is able to prove statistically significant events and statistically valid arguments. Normally, this person would have modeling skills with Matlab, R, or perhaps SAS, and they should also have some programming/scripting skills with C++ or Python. It really depends on your whole environment and the flow of data. In my experience, Data Scientists that exclusively use SAS are sometimes extremely skilled PhD level statisticians and focused exclusively on the accuracy of the models (which is okay), but often not sufficiently skilled to fit within an early startup's big data environment in today's world and handle all of the responsibilities you'd like them to handle described in your question. I'm am not bad mouthing SAS people as they are often the MOST talented mathematicians and I have a great deal of respect for their minds, but if they do not have the programming skills, they become isolated within a group without a Data Engineer helping them along. Often a SAS user trying to fit into this environment will force you to use a stack of technologies that a skilled Data Architect would not recommend using. It takes programming in some object oriented language to fit into today's big data environments, and the better Data Scientists are using hybrid functional and OOP programming languages like Scala. Extremely hard to find Data Scientist can also work with graph databases like Neo4j, Titan, or Apache Giraph.
2. The Data Engineer, if you're dealing with a firehose of data like Twitter and capturing it into a NoSQL architecture, this is the person who would prepare the data for the Data Scientist to analyze. They often are capable of using machine learning libraries like WEKA to transform data, or techniques like MapReduce on Hadoop.
3. The Data Modeler/Analyst is someone who can use a tool like SAS, SPSS, Matlab, or even R, probably a very strong advanced Excel user, but likely won't be a strong programmer, although perhaps they will have a computer science degree and have some academic programming experience.
The most important thing to watch out for is someone who is too academic, and has not been proven to deliver a solution in the real world. This will really screw you up if you're a startup, and could be the reason you fail. Often, the startup will run out of money due to the time it takes to deliver a complete solution or in the startup's case, a minimally viable product. Ask for examples of their work, and specifically dig into what it is that they did for that solution.
I've tried to cover a pretty broad range of possibilities here, but it's best to talk in specifics. I'd be happy to discuss this with you in detail. To answer your question, is it perfectly reasonable for someone to handle all of the responsibilities described in your question, if you find the right type of person with the appropriate skills, and a history of success.
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