Careers: Product Manager

Are you looking for the chance to drive an innovative product and make a real impact? This role is an ideal opportunity to move the needle on some serious businesses and improve the customer experience of millions of people. Causata’s clients are among the largest Fortune 500 retail and financial services companies.

Working at Causata you’ll see how ‘big data’ and cutting-edge machine learning technology are revolutionizing how businesses interact with consumers. You’ll play a pivotal role in Causata’s success and become an expert in real-time customer intelligence. You’ll also get the opportunity to work alongside other highly talented individuals.

As a product manager you will be the primary advocate for our customers with product development activities. You must possess a balance of business and technical savvy, a big-picture vision, and the drive to make that a reality.

Responsibilities:
• Synthesizing clear and detailed product requirements for effective collaboration with the design and engineering team
• Ongoing visits to customers and other companies in our industry to validate needs and pain points and couple that information into the requirements
• Providing consistent dedicated energy to ensuring the product evolves at a rapid pace.
• Working with design and engineering teams to plan, organize and deliver impressive product releases with high quality
• Maintaining the roadmap
• Competitive analysis

Requirements:
• A passion for customers, technology innovation and product excellence
• Strong oral and written communicator with all types of audiences
• 4+ years of software product management experience with battle-tested skills in requirements gathering, release management, and software delivery
• Exceptional skills listening to customers and transforming their feedback into business requirements that result in successful products
• Proven ability to collaborate with counterparts in client services, design and engineering
• Direct exposure to large Fortune 500 enterprise clients (a knowledge of consumer oriented retail and financial services companies is a strong plus)
• Willingness to travel - up to 50%, spending time in both our San Mateo and London offices
• Good knowledge of statistics and how data and analytics can be used in both marketing and non-marketing contexts to drive business performance and improved customer experiences
• Science, Computer Science or Engineering degree

Visit Careers to apply.

Careers: Senior Interaction/UX Designer

Causata, Inc. is recruiting a London-based Senior Interaction/UX Designer to join our venture-backed startup. This challenging role involves creating a web-based user interface for a product that is used to visualize massive amounts of complex data. You'll be working with the latest technologies and on a ground-breaking product.

We know that a great user experience is at the heart of any successful product. As our Senior Interaction Designer we want you to be a driving force in gathering insight into our users' needs, behaviors and intentions. You'll be translating this into innovative interface designs for state-of-the-art software that enables our users to explore and interact with huge amounts of data. You will be responsible for the UX and the UI working closely with (and managing) a visual designer, engineers and the product team throughout all stages of the product cycle.

Responsibilities:
• Taking part in requirements gathering and user research.
• Defining the user and interaction model.
• Creating a detailed user interface design for all our products.
• Developing high level and/or detailed storyboards, mockups and prototypes to effectively communicate interaction and design ideas.
• Championing user needs and the overall user experience.

Requirements:
• Solid academic background, Masters degree or equivalent experience, specializing in design, human-computer interaction, ergonomics, computer science or cognitive psychology.
• At least five years experience in application design, online interaction design or information architecture.
• Outstanding conceptual design skills and familiarity with high-level deliverables (scenarios, personas, flow diagrams, etc.) as well as low-level interaction design best practice.
• Skilled in at least one method of UI prototyping (Axure, Flash Catalyst, Flex, Fireworks, Illustrator, JavaScript frameworks etc.)
• Contribute to the creation of our product roadmap.
• Rationalize design decisions to stakeholders and peers.
• Create detailed specifications as needed.
• Enthusiasm for IxD, UX, and IA with a broad knowledge of current practice.
• Excellent leadership, communication and teamwork skills.
• Experience or interest in data visualisation and statistical analysis tools would be highly beneficial.

Visit Careers to apply.

The Evolving Enterprise

"We have only two sources of competitive advantage:
1. The ability to learn more about our customers faster than the competition
2. The ability to turn that learning into action faster than the competition"

Quotation is attributed to Jack Welch, CEO General Electric

If Jack Welch’s assertions are true (and I believe they are) then
there is a major disconnect between the way enterprises currently
think about data management and how they should be thinking about it.
If rapid learning from customer data and acting upon that learning are
the only real sources of competitive advantage then why aren’t
enterprises worrying much more about organizing data to efficiently do
just that? Why is the focus of data management today on basic tasks
such as storage, retrieval and querying for reporting? This can’t be
right.

I expect this situation to change quickly. Over the last few years
there has been a rapidly accelerating effort on developing powerful
new analytical architectures, and these technologies are creating a
growing appreciation that enterprise data has been an enormous
unrealized asset.

If monetary value really can be extracted from new analytical
technologies in a way that very quickly generates returns of many
times cost, then enterprises will be quick to implement these new
technologies. What enterprises need right now more than anything else
is hard evidence that this can actually be done.

Rather tantalizingly, what we will see in this accelerating market are
widening gaps between the technically possible and the commercially
proven, and between the commercially proven and published case studies
in the public domain.

Here at Causata we like Jack Welch's words quoted above. It would be
hard to more succinctly express the essence of what Causata's software
encapsulates as a product than Welch’s points 1 and 2.

Paul.

Big Answers

In a recent Economist story two striking facts extracted from Big Data were reported:

Best Buy, a retailer, found that 7% of its customers accounted for 43% of its sales.

and

In Britain the Royal Shakespeare Company (RSC) sifted through seven years of sales data for a marketing campaign that increased regular visitors by 70%.

And it's not hard to find other stories indicating that enormous gains in revenue can be extracted from the data that companies already have. For example, the web site NapaStyle.com reports a 10% lift in revenue per visitor after two months of mining customer clicks to understand behavior. World Kitchen reported an average order value increase of 20% using similar technology.

Anecdotal evidence says that Amazon.com is getting an additional 10% sales revenue by mining the books that its customers buy to recommend other titles they might like. And Netflix gets 60% of its rentals from people clicking through on similarly mined data guiding its recommendations.

Startup FlightCaster is taking a Big Data approach mining airline records, weather and FAA real-time traffic information to provide accurate predictions of flight delays well ahead of the airlines themselves. Their application provides flight delay information 6 hours before the airlines tell their own customers.

Fox Audience Network, which handles advertising across all Fox properties (including MySpace), is using a large cluster of machines crunching Big Data to obtain an order of magnitude increase in advertising margins.

And Europe's largest ad targeting network, nugg.ad is using Big Data to drive everything they do.

Users of Big Data shouldn't be surprised by Big Answers: Big Data represents a massive untapped resource that all companies already have. It's just a question of integrating the right software to obtain Big Answers.

John.

The Economist catches the Big Data wave

At Causata we spend all our time with Big Data and so it's nice to see the Economist (current issue) produce a special report (written by Kenneth Cukier) about the explosion of data and the technologies needed to process it.

The business of information management—helping organisations to make sense of their proliferating data—is growing by leaps and bounds. In recent years Oracle, IBM, Microsoft and SAP between them have spent more than $15 billion on buying software firms specialising in data management and analytics. This industry is estimated to be worth more than $100 billion and growing at almost 10% a year, roughly twice as fast as the software business as a whole.

In addition to the special report there's an interview with the report's author:

Part of the Economist article was driven by a report from O'Reilly called Big Data: Technologies and Techniques for Large-Scale Data.

O'Reilly produced a set of interviews to accompany that report. Here's the first:

The rest can be found here.

John.

So you think machine learning is boring?

If you say the words 'machine learning' to people they either look confused or bored. Since the promise of Artificial Intelligence evaporated in the 1970s, machine intelligence seems to be one of those things that's a perpetual 20 years away.

There's a lot happening in machine learning: the next ten years should be very exciting

But computer industry insiders know that many forms of machine learning are at work all the time. The most common and visible are recommendation systems like the one on Amazon.com that comes up with suggestions for other books you might like. But even that doesn't express the true power of state of the art algorithms.

But a helicopter doing backflips and a walking robot do.

Here's AnyBots walking robot Dexter taking his first steps. Dexter is unusual in that unlike other walking robots he's essentially unstable (just like a human). He needs to constantly adjust his 'muscles' to stay upright. And he wasn't programmed to walk like that, he was programmed to learn to stay upright and walk.



And here's the Stanford University Autonomous Helicopter doing some stomach churning maneuvers. The helicopter is flying itself and being instructed to perform tricks for the camera. It learned to perform these tricks by learning to emulate the trajectory of a real helicopter flown by a human.



And if you've seen Lord of the Rings or Troy, or played Grand Theft Auto IV then you've seen a different sort of machine learning in action. Human motion in stunts in the films, and by characters in the game, are driven by algorithms that were created via computer evolution.



There's a lot happening in machine learning: the next ten years should be very exciting.

John.

Benchmarking - KDD and Netflix

Machine learning and statistical methods are at the heart of what we do. They absolutely are. This is because we’re striving for the most accurate answers, with a latency that makes them commercially valuable. Creating the best engineered solution that delivers undisputed value is what we are about. In our world if it doesn’t provide a measurable performance improvement for the task at hand then it isn’t useful.

We apply the discipline of benchmarking in almost everything we do (...it may not surprise you that we operate as a true meritocracy at Causata... I absolutely believe that if somebody can do my job better than me then they should be doing it...!!) It keeps us focused and real. I recall some early days in 1997 and 1998 when I was privileged to work with two exceptional database marketing practitioners, Jacob Zahavi and Nissan Levin. They wrote some software at Urban Science that won the KDD cup for two years running. A significant difference between their approach and their more academic competitors was that these guys ruthlessly benchmarked everything they did against previous work, using large representative data sets. This prevented unfounded preferences in their methods arising through familiarity, discouraged misplaced pride, and encouraged the exploration of new techniques.

The frantic developments leading up to the Netflix prize on 26th July 2009 were a very public demonstration of the power of transparent benchmarking in developing engineering solutions for decision science. The ranking of performance clearly accelerated the validation of approaches that worked well and helped identify new hybrid opportunities.

It is huge fun working with talented and energized people in developing new solutions, but I have learned to respect benchmarking and champion challenge as processes that keep us grounded and drive engineering progress.

Paul.