Invests in
Sectors:
Locations:
Min Investment:
$200,000.00Max Investment:
$300,000.00Target Investment:
$250,000.00
Skills
Education
Lists including Tristan
Work Experience
2022
Co-Founder & CEO
2022
Venture-backed stealth mode.
2017
Venture Partner
2017
Investor and Advisor. Fund I and III.
2019
Angel Investor
2019
Rain.AI SuperMove Rora, Inc Edge (payment) answersai.com Various stealth
2017 - 2022
Advisor
2022 - 2022
Continued consultation for the organization I left behind, as well as advisory to the CEO on topics including GM and M&A.
Vice President of Solutions
2020 - 2022
I helped scale GTM @ Iterable for pre and postsales from $5m to $120m+ ARR over 5 years by owning functional areas including: - Solutions Consulting - Solutions Architecture - Value Consulting - Demo Engineering Some additional responsibilities include: - COGS / margin / pricing - Analyst relations (Forrester / Gartner) - Drove early-stage product roadmap (Series B/C) - Late-stage fundraising (Series C/D/E)
Senior Director, Solutions
2019 - 2020
Leader of our pre-sales Solutions Consulting teams and post-sales Solutions Architect team spanning SF, Denver, NY, and UK.
Director of Solutions Consulting
2017 - 2019
Leader of our pre-sales Solutions Consulting team.
Sales Engineering Lead
2017 - 2017
First one in the arena.
2021 - 2021
Leadership Council Member
2021 - 2021
I had the honor of serving on the inaugural leadership council for PreSales Leadership Collective over an annual term.
2014 - 2019
Co-Founder & CTO (YC S15)
2014 - 2019
Product | Engineering | Sales Leada is a venture/Y Combinator backed online education Saas startup based in SF. We are trusted by some of the best universities around the world. Tech - Continuously design, build, and iterate on the product (https://www.teamleada.com/) based on user feedback. - Ran A/B test to drive ~3x increase in demo requests. - Oversaw migration from Heroku to AWS, leading to $15k in quarterly cost saving. - Manage deployments on AWS to ensure 99.999% uptime. Sales / Marketing: - Built out a repeatable inside sales process. - Grew lead generated by 5x in less than 3 months with zero added cost. - Closed $100k+ in sales. - Development of (http://analyticshandbook.com/ 50k+ downloads) to drive organic traffic. Recruiting / Management: - Recruit and manage SDR/lead gen to build a predictable pipeline - Recruit and manage a software delivery team that led to high CSAT with customers like Zenefits, Twitch, and TeeSpring. - Recruit and manage curriculum developers for Python and SQL courses, which became our largest enterprise revenue driver. - Manage engineers and contractors to ensure agile feature delivery. Full time until Jan 2017, part time after.
2016 - 2017
Business Development
2016 - 2017
Pioneered partnerships with industry leaders including Deloitte, Wipro, and the Auto ISAC. This was a special short term role reporting directly to the CEO.
2016 - 2016
Interim CTO
2016 - 2016
YCS15 batchmate. (Acq. by Glam&Go in 2017). Interim CTO to lead technical projects including: - Successfully plan and implement a full Braze Integration - Successfully plan and implement FriendBuy referral integration - Technical debt payoff via documentation/test plans - Advise the CEO on tech stack
2013 - 2013
Software Engineering, Security and Compliance Solutions
2013 - 2013
Built a full featured Splunk app that allows for consumption, visualization and analysis of Cisco NetFlow data exports. Some features inculde: • Predictive analytics of various network traffic utilizing machine learning algorithms (built on top of BSD-licensed 3rd party python libraries). The algorithms offered better prediction than the default built-in Splunk “predict” command which leverages kalman filters. • Fast visualization of GB of data through Splunk’s experimental tool, tsidx. • Continuous real-time network monitoring capability.
2012 - 2013
Data Science
2012 - 2013
• Designed and built a company popularity ranking model through text sentiment analysis. The project required analysis of 200GB+ of unstructured text data as well as structured intra-day text click data. The tools used include Hadoop (MapReduce as well as custom-built UDAF on Hive), R, Java, Open Calais (for NLP), and Python. The model performed better than the existing model in several metrics. • Improved automation and monitoring by creating automated server redeployment and backup tools via Fabric. It came in handy when I torched a production server. Valuable lessons were learned. • Maintained and upgraded legacy code.