Lead Data Engineer, Machine Learning & Pipelining

New York
US$210000 - US$230000 per annum

LEAD DATA ENGINEER, MACHINE LEARNING & PIPELINING

$210,000 - $230,000 + benefits

New York City

Are you an experienced data engineer who loves video gaming analytics? This is an exciting opportunity to lead a team utilizing machine learning to build a cutting-edge gaming analytics platform. You will be collaborating to build data pipelines and models, as well as advising major business decisions by working with various stakeholders.

THE COMPANY:

You will be in a senior role for one of the most renowned video game companies in the United States. They consistently incorporate innovative technologies in Machine Learning and Gaming Analytics to maintain a competitive edge. You will be immersed in creativity and have new opportunities to learn from some of the most talented people in the industry. With over 4 stars on Glassdoor, the passionate employees here value inclusion, collaboration, and support.

THE ROLE:

As the Lead Data Engineer in Modeling & Machine Learning, you will have a senior role in the company working with C-level executives on data engineering strategies. You'll be coaching a team of world-class data engineers, and be responsible for screening and hiring top talent. If you have a passion for the video game industry, and love combining technical machine learning & pipelining with strategic business plans, then this is the perfect role for you!

Some of the day to day responsibilities of this role are:

  • Lead the development of data models/aggregations, machine learning pipelines, machine learning feature stores, and data products
  • Work with C-level executives to translate the technical information into business strategies
  • Implement end-to-end solutions for batch and real-time algorithms
  • Oversee monitoring, logging, automated testing, performance testing and A/B testing.
  • Lead, manage and coach a team of world-class data engineers
  • Participate in the recruitment of top data engineers

YOUR SKILLS AND EXPERIENCE:

The best candidates will have the following skills and experience:

  • Previously worked in the video game industry
  • Significant experience managing or supervising a team
  • Significant commercial experience in ETL, big data architecture, big data technology
  • Strong Proficiency in Python, Hadoop, & Spark, having utilized this in a commercial role previously
  • Ability to explain technical information to business leaders

THE BENEFITS:

  • Competitive PTO
  • Healthcare & 410k
  • Unique Culture
  • Flexibility

HOW TO APPLY:

Please register your interest by sending your CV to Nitasha Khazanchi via the Apply link on this page

Send similar jobs by email
NK/98879
New York
US$210000 - US$230000 per annum
  1. Permanent
  2. Deep Learning and AI

Similar Jobs

Salary

US$880 - US$1600 per day + benefits

Location

New York

Description

Looking for a lead machine learning engineer who can lead a bot mitigation project working with stream data for a global sportswear leader.

Salary

US$480 - US$720 per day

Location

California

Description

Join this leading retailer as a machine learning engineering helping scale and productionalize models around bot detection.

Salary

US$200000 - US$250000 per annum + Bonus, Benefits, 401k

Location

San Francisco, California

Description

Exciting opportunity to join a successful organization within healthcare. You will be involved in driving the business forward and make an immediate impact.

Salary

US$210000 - US$230000 per annum + bonus, benefits, unlimited vacation

Location

San Francisco, California

Description

Looking for a machine learning scientist with experience working alongside chemists! Remote ok

Harnham blog & news

With over 10 years experience working solely in the Data & Analytics sector our consultants are able to offer detailed insights into the industry.

Visit our Blogs & News portal or check out our recent posts below.

Black History Month: Ethical AI and the Bias Within

According to Brigette Hyacinth’s 2017 book entitled, The Future of Leadership, the author suggests this when considering the ramifications of AI. “Using AI to improve efficiency is one thing, using it to judge people isn’t something I would support. It violates the intention on the applications of AI. This seems to be social prejudice masquerading as science…” How often have big tech companies backtracked their facial recognition software? What are the ethical implications of moving forward and leaving AI unchecked and unregulated? 2020 was in no way a traditional year amassing change on our daily lives at near lightspeed, or so it seemed. But what was brought to bear were unrest and tensions boiled to the breaking point. And when you look at it from the perspective of AI in our daily lives. What might the world look like in another year? When Social Sciences and Humanities Meets AI “To err is human, to forgive, divine.” Humans make mistakes. Biases are unmasked with and without intent. But, when it comes to AI, those unintentional biases can have devastating consequences. From 2015 to 2019, use of AI grew by over 250 percent and is projected to boast a revenue of over $100 billion by 2025. As major businesses such as Amazon and IBM cancel and suspend their facial recognition programs amidst protests against racial inequality, some realize more than regulatory change is needed. Since 2014, algorithms have shown biases against people of color and between genders. In a recent article from Time.com, a researcher showed the inaccuracies of prediction for women of color, in particular. Oprah Winfrey, Michelle Obama, and Serena Williams skewed as male. Three of the most recognizable faces in the world and AI algorithms missed the mark. These are the same algorithm and machine learning principles used to challenge humans at strategy games such as Chess and Go. Where’s the disconnect? According to one author, it may be time to create a new field of study specific to AI. Though created in Computer Science and Computer Engineering labs, the complexities of human are more often discussed in the field of humanities. To expand further as well into business schools, race and gender studies, and political science departments. How Did We Get Here? At first blush, it may not seem comparable to consider human history with the rise of artificial intelligence and its applications. Yet it’s human history and its social construct which explains the racial and gender biases when it comes to ethics in AI. How deep seated are such biases? What drives the inequalities when AI-enabled algorithms pass over people of color and women in job searches, credit scores, or assume status quo in incarceration statistics? Disparities between rational and relational are the cornerstone from which to begin. Once again, in Hyacinth’s book, The Future of Leadership, the author tells a story of her mother explaining the community around the simple task of washing clothes. Though washing machines now exist and do allow people to do other things while the clothes are washed, there is a key element recounted by her mother washing machines lack. The benefit of community. When her mother washed clothes, it was her and her surrounding community. They gathered to wash, to visit, and connect. A job was completed, but the experience lingered on. And in the invention of a single machine, that particular bit of community was lost. But it’s community and collaboration which remind humans of their humanity. And it’s from these psychological and sociological roles, artificial intelligence should learn. Create connections between those build the systems and those who will use them.  BUILDING AI FORWARD Voices once shuttered and subjugated have opened doors to move artificial intelligence forward. It is the quintessence of ‘those who don’t know their history are doomed to repeat it’. The difference within this scientific equivalent is there is no history to repeat when it comes to technology. And so it is from the humanitarian angle AI is considered. The ability to do great things with technology is writ in books and screenplays, and so are its dangers. While it isn’t likely an overabundance of ‘Mr. Smiths’ will fill our world, it is important we continue to break out of the siloes of science versus social sciences. If AI is to help humanity move forward, it’s important to ensure humanity plays a role in teaching our machine learning systems how different we are from each other and to consider the whole person, not just their exoskeleton. If you’re interested in the Data Sciences, Data and Technology, Machine Learning, or Robotics just to name a few, Harnham may have a role for you. Check out our current vacancies or contact one of our expert consultants to learn more.  For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.  For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.  

Puzzle and Problem-Solvers: Software Engineers Drive Business

Software. It’s the drivers to your printer. It’s the word processor on your PC. And it’s the concept behind your productivity tools, your CRM systems, and your social media programs. Software engineers are to software what Data Engineers are to Data.  Software Engineers are the creators, builders, and maintainers of software systems and programs, so business runs smoothly. Now, that the majority of businesses have shifted online, it’s more important than ever to keep things running smoothly. These engineers must take into account not only what businesses might need to run, but also the limitations of the program. It’s a balancing act of software, hardware, limitations, and possibilities. If you took apart watches as a kid to see how they worked, Software Engineering might be for you. Are you a problem solver? Do you love putting the pieces of a puzzle together whether it’s on a board or in a crossword? Software Engineering might be for you. What Kind of Software Engineer are You? While there are a variety of roles to consider, below are some of the more popular paths taken. So, let’s say you want to build computer applications that affect what the end user sees. If you know programming languages such as Python and Java, and understand the mechanics of how to make a program work, then you may fit the classic example of a Software Engineer. If you’re more interested in the focus of robotics or automation, you may want to consider a role in Embedded Systems. You’ll still be designing, developing, and maintaining but your projects will be hardware and software used for a specific task.   Want to keep information secure? You may lean toward Security Engineer. In this role, you’ll ensure there are no security flaws. How? By operating as a ‘white-hat’ ethical hacker to attempt breaking into existing systems to identify threats. Technical Skills are Essential. Soft Skills are Important.  For anyone in the Data professions, technical skills are paramount. This not only gets your ‘foot in the door’, but ensures you know the basics. And for those who’ve been in the game a bit longer, also gives businesses confidence you can meet any challenges which may come up. Technical skills for Software Engineers include knowing programming languages like C++, Python, Java, and others like them. In this role, you’ll need to understand development processes as well as additional technical concepts. Technical skills are a standard requirement. And as important as it is to have a good portfolio and experience, you’ll want to show the business, you have the technical know-how to take on anything which may come your way. Now that cross-functional teams across departments are regular occurrences and C-suite executives are in the know, soft skills are just as important as technical skills. What are Soft Skills? In a nutshell, soft skills are communication skills. In the past, Data professionals may have been siloed away from other teams, and a liaison of sorts might have translated Data information into actionable insights. Now businesses and professionals have found it’s much more efficient to have the Engineer speak directly to their team, their leadership, or stakeholders. So, it’s imperative your soft skills are on par with your technical skills. Scope of Work for a Software Engineer According to the Bureau of Labor Statistics, Software Engineer employment growth is expected to grow 21 percent by 2028. Now that we’re working, studying, and socializing online more than ever, is it any wonder? Add to this the changing needs of organizations as they shift their practices into the cloud, and it’s more important than ever to have professionals who can design and maintain software to meet the needs of an organization. Whichever avenue you choose, whichever business you join or career path you follow, the full scope of work will be broad. You could be in charge of creating, developing, and maintaining a full product or just a single component of an app. Regardless of your scope of work, though, you’ll most likely be working with developers, cross-departmental staff, executives, clients, and stakeholders to mold, shape, and fulfill a design envisioned for their product. If you’re interested in the Data Science, Data Technology, Machine Learning, or Software Engineering, Harnham may have a role for you. Check out our current vacancies or contact one of our expert consultants to learn more.  For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.  For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.  

Recently Viewed jobs