Sociogramics, Inc. Jobs on Startuply

Run Engineering at Hot Startup in Mountain View

Tue, 21 May 2013 20:54:37 GMT

Sociogramics is a venture-backed company that is breaking new ground in leveraging the expanding social graph into actionable information for financial services companies. The team has prior start-up experience across a mix of verticals to include cleanteach, financial services, education, consumer internet and online dating. We are backed by several ventures funds and located in the friendly Old Palo Alto Downtown near the California Avenue CalTrain station.

You must LOVE technology and be able to prove it
You live to architect, design, manage, and hire the construction workers as well as lay the bricks
Understand startup compensation (low cash with equity upside)
You are able and willing to work long hours with a great team of fun people

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Co-Founder and CTO in Mountain View

Mon, 20 May 2013 18:34:26 GMT

Sociogramics is pioneering new methods for measuring financial character and credibility through a unique mash-up of social graph, behavioral economics, emerging APIs and other methods. The goal is to bring new credit opportunities to the 80 million Americans classified as the “underbanked” especially immigrants, youth and those new to credit. You will be the technical leader in an early stage company (4 employees) with venture capital seed investors, sufficient capital until next round (one year of cash) and intense commercial interest from industry leading financial institutions and traditional data providers. If you are keen on making a difference to those less fortunate while diving deep into new complex challenges, then Sociogramics is firmly in your sweet spot!

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Lead Software Developer in Mountain View

Thu, 09 May 2013 05:56:07 GMT

Sociogramics is a growing, seed stage financial technology company backed by 5 leading venture capital firms. The Company is breaking new ground in leveraging the social graph into actionable information for financial services companies with the goal of bringing credit to the unbanked, under-banked, new immigrants and youthful markets. The team has prior start-up experience across a mix of verticals to include cleantech, financial services, education, consumer internet, social media and online dating (founder of Match.Com is the founder here). We are located in Mountain View near the San Antonio CalTrain station.

You must LOVE technology and be able to prove it

You might have experience in following areas:
FinTech - worked with or for PayPal, Fair Isaac, First Data, Jack Henry, Acxiom, Fidelity National Information Services, Fiserv, or other companies selling to credit granters

Consumer Behavior - companies using behavioral analytics such as oPower, Progressive or Visa

Machine Learning - analysis of massive unstructured (Big Data) datasets to discover signals (e.g. Bayesian networks that learn) that produce otherwise hidden insights

Prior start-up experience very important:
You must have been in at least one startup under 20 people for a material period of time
Understand startup compensation (low cash with equity upside)
You are able and willing to work long hours with a great team of fun people
Meticulous determination to solve extremely hard problems and never give up!

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Java Developer @ Big Data Fintech Startup in Mountain View

Fri, 03 May 2013 22:19:26 GMT

Sociogramics launched in 2011 on the premise that existing scores and methods for sorting and assigning consumer behaviors are obsolete in an era of Big Data. We are leveraging emerging data sets coupled with our team's machine learning expertise to fundamentally improve online identity verification and micro-segment probable consumer behaviors across multiple dimensions. Our first target vertical is financial services as it is a data rich environment with surprisingly poor individual-level prediction tools. We are already providing a 10x ROI to our first lending customers as compared to existing services.

Why does this matter? Current solutions are blunt force tools that rely on mass segmentation to bucket individuals together in false cohorts that are used to inform decisions ranging from who receives an offer of credit, who is approved for credit, what types of products are offered and when and ultimately that person's profit potential to the financial institution. The more individual-level information we can make available to our customers the more effectively they can acquire and service new and existing customers = more options, opportunities and better pricing for consumers.

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