Principal Data Scientist

San Francisco, California
US$200000 - US$240000 per year

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Principal Data Scientist

Harnham are currently partnering with a market leading business, disrupting their industry and generating substantial impact through the implementation of Deep Learning solutions in their continued growth of a best-in-class Data Science team.

Based out of downtown San Francisco, you'll be working with an innovative, AI first, Data Science team backed by one of the largest PE firms in the world.

If you're someone who wants to work in a collaborative environment, where you'll see your work go into production and make substantial changes, while directly benefiting from the value that you generate. This is the place for you.

YOUR ROLE AS PRINCIPAL DATA SCIENTIST:

  • Design and implement deployable deep learning solutions that have genuine enterprise level impact.
  • Evaluate and deliver visionary solutions to apply to various business problems, focusing on adding value and AI led automation.
  • Be the lead for the ideation, prototyping and deployment of state-of-the-art, Neural Networks, leveraging the latest developments in Deep learning & Computer Vision
  • Work with non technical stakeholders on the development and execution of product decisions and launches.
  • Identify promising new areas for continued research & development.

SKILLS AND EXPERIENCE:

  • PhD in a quantitative discipline such as: Statistics, Maths, Computer Science or Engineering (Master's degree considered)
  • At least 5 years of experience of working with Deep learning methodologies
  • Extensive experience and understanding of Machine Learning Techniques
  • Experience of working within an AWS environment
  • Previous experience working with Tensorflow & Keras
  • Prior exposure to NLP methodologies & toolkits would be a plus
  • World Class communication skills

THE BENEFITS:

A base salary of between $200,000 - $240,000 as well as a performance related annual bonus and a first of it's kind incentive program with potentially limitless upside.

HOW TO APPLY:

Please register your interest in this Principal Data Scientist role by sending your résumé via the' Apply' link on this page.

KEYWORDS

Data Science, Data Scientist, Deep Learning, Tensorflow, Neural Networks, Big Data, R, SQL, Python, Insight, Analytics, Data, Statistics, Modelling, Machine Learning, Algorithms, Bayesian

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28047
San Francisco, California
US$200000 - US$240000 per year

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The Advantages And Disadvantages Of Computer Vision

The Advantages And Disadvantages Of Computer Vision

“Don’t judge a book by its cover”. We use this adage to remind ourselves to go deeper and to look beyond the superficial exterior. Except, sometimes, we can’t, or won’t. Sometimes, our perceptions are pre-programmed. Think family, peer pressure, and social influences. But what about computers? What do they see? In a digital landscape that demands privacy but needs information, what are the advantages and disadvantages of Computer Vision? The Good: Digital Superpowers  Let’s be clear, Computer Vision is not the same as image recognition, though they are often used interchangeably. Computer Vision is more than looking at pictures, it is closer to a superpower. It can see in the dark, through walls, and over long distances and, in a matter of moments, rifle through massive volumes of information and report back its findings. So, what does this mean? First and foremost, it means Computer Vision can support us in our daily activities and business. It may not seem like it at first glance, but much of what the computer sees is to our advantage. Let’s take a deeper look into the ways we use Computer Vision today. Big Data: From backup cameras on cars to traffic patterns, weather reports to shopping behaviours and everything in between. Everything we do, professional to personal, is being watched, recorded, and used for warning, learning, saving, spending, and social. Geo-Location: Want to know how to get from Point A to Point B? This is where Geo-location comes in. In order to navigate, the satellite must first pinpoint where we are and along the way, it can point out restaurants, shops, and services to ease us on our way.Medical Imaging: X-rays, ultrasounds, catheterisations, MRIs, CAT Scans, even LASIK are already in use. Add telemedicine and the possibilities are endless. The application of these functions will allow faster and more accurate diagnoses and help save lives.Sensors: Motion sensors that only turns a light on when a heat signature is nearby are already saving your home or business money on your electric bill. Now, during a shop visit when you are eyeing an intriguing product, your phone may buzz with a coupon for that very item. Computer Vision sensors are now tracking shopper movements to help optimize your shopping experience.Thermal Imaging: Heat signatures already help humans detect heat or gas and avoid dangerous areas, but soon this function will be integrated into every smart phone. Thermal imaging is no longer used just to catch dangerous environments, it’s used in sport. From determining drug use to statistics and strategy, this is yet another example . The Bad: Privacy Will Forever Change  Google is 20 years old this year. Facebook is 15. Between these two media tech giants, technological advances have ratcheted steadily toward the Catch-22 of both helping our daily lives, whilst exposing our data to our employers, governments, and advertisers. Computer Vision will allow them to see you and what you’re doing in photos and may make decisions based on something you did in your school or university days. We’re already pre-wired to make snap judgements and judge books by their cover, but what will these advancements do to our daily lives? Privacy will change forever.  We document our lives daily with little regard to the privacy settings on our favourite social media apps. GDPR has been a good start, but it’s deigned to protect businesses and create trust from consumers, rather than truly offer privacy. So far, the impact on our privacy has been limited as it still takes such a long time to sift through the amount of data available. However, the time is coming soon, where we’ll need to perhaps think of a privacy regulation businesses, employers, and governments must follow to protect the general population. Fahrenheit 451, 1984, and Animal Farm were once cautionary tales of a far-off future. But Big Brother is already watching and has been for quite some time. Police monitor YouTube videos. Mayors cite tweets to justify their actions. And we, thumb through our phones tagging friends and family without discretion.  Like every new technological advancement there are advantages and disadvantages. As Computer Vision becomes increasingly prevalent, we’ll all need to be aware of the kind of data we supply from to text to image. We can’t go back to the way things were, but we can learn about ourselves through the computer’s lens. And when it comes to computers and their capabilities, don’t judge a book its cover. If you’re interested in Data & Analytics, we may have a role for you. Take a look at our latest opportunities or get in touch with one of our expert consultants for more information. 

How To Attract Data Scientists To Your Business (And How Not To)

How To Attract Data Scientists To Your Business (And How Not To)

Whilst the role of Data Scientist is still considered one of the most desirable around, many businesses are finding that a shortage of strong, experienced talent is preventing them from growing their teams sufficiently. With a huge demand for such a small talent base, enterprises have begun to ask what they can do to ensure that they can secure the skillsets they need.  If you’re looking at hiring a Data Scientist, there are a few key Do’s and Don’ts that you need to bear in mind: THE DO’S Create A Clear Career Path In most companies, a career path is defined. Usually you grow from junior to senior to manager etc. However, Data Scientists often like to become experts rather than moving up the traditional career ladder into people management roles. And, once a Data Scientists becomes an expert, they want to remain an expert. To do this, they need to keep up with the latest tools and data systems and continually improve. That’s why it’s important that you put in place a clear career path that suits the Data Scientists. In addition to the possibility of leading teams on projects, businesses should provide opportunities for financial progression that reflect growing skillsets in addition to increased responsibilities.  Let Them Be Inventive One of the biggest turn-offs for Data Scientists is lack of opportunities to try new techniques and technologies. Data Scientists can get bored easily if their tasks are not challenging enough. They want to work on a company’s most important and challenging functions and feel as though they are making an impact. If they are asked to spend their time on performing the same tasks all the time, they often feel under-utilised. Providing forward-looking projects, with innovative technologies, gives Data Scientists the opportunity to reinvent the way the company benefits from their Data. Provide Opportunities To Discover  As part of their attitude of constant improvement, Data Scientists often feel that attending conferences or meet-ups helps them become better at their role. Not only are these a chance for them to meet with their peers and exchange their Data Science knowledge, they can also discover new algorithms and methodologies that could be of benefit to your business. Businesses that allow the time and budget for their team to attend these are seen as much more attractive prospects for potential employees in a competitive market.  Give them the freedom they need Data Scientists are efficient workers who can both collaborate and work independently. Because of this, they expect their employers to trust that they will get the job done without feeling micro-managed. By offering flexible working, be it flexi-hours or working from home options, enterprises can make themselves a much more appealing place to work.  THE DON’TS Hire The Wrong Skillset As many companies begin to introduce Data teams into their business, they can often attempt to hire for the wrong job. Generally, this will be because they automatically jump to wanting to hire a Data Scientist, but actually need a different role placed first. For example; a company may be looking to hire a Machine Learning specialist, but their data pipeline hasn't even been built yet. There are many talented candidates out there who want to work with the latest technology and solve problems in complex ways. But the reality is that a lot of businesses aren’t ready for their capabilities yet. Before hiring, asses what skillsets you really need and be specific in your search.  Undervalue Their Capabilities  There are still a large number of organisations that do not value Data within their culture and Data professionals pick up on this incredibly quickly. If they feel that their work is under appreciated, and they know that there is high demand for what they do, they will not waste their time sticking around. Ask yourself how you see your Data team contributing to the company as a whole and make this clear within your organisation. Advanced Data Scientists don't want to work on dashboarding so make sure that their work will have an impact and explain how you see this happening during the interview process. Additionally, be aware of other financial implications that their hire may have. It’s likely that they’ll need a supporting Data Engineer to work with and, if they don’t have access to one, they have another reason to look elsewhere.  The Data Scientist market is a candidate-driven one and, as a result of this, businesses need to go the extra mile to ensure they get the best talent around. By offering a strong set of benefits, the opportunity to grow and progress, and an environment that values Data, enterprises can stand out amongst the crowd and attract the best Data Scientists on the market.  If you’re looking for support with your Data Science hiring process, get in touch with one of our expert consultants who will be able to advise you on the best way forward. 

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