Senior Manager, Gameplay Analytics

New York
Negotiable

Senior Manager, Gameplay Analytics
Video Games
New York, NY
$165,000 to $185,000

Do you consider yourself a gamer and have a passion for joining an innovative team that is responsible for creating some of the most popular games across the globe? A leading online gaming company is looking for an experienced Senior Manager, Gameplay Analytics to spearhead the analysis of user behavior as well as the predictive modeling needed to meet business growth in New York.

THE ROLE:

As Senior Manager, Gameplay Analytics, you will be the Advanced Analytics lead in analyzing large amounts of consumer data and building predictive models to make data-driven recommendations about what games will be popular next. You will be responsible for:

  • Collecting, cleaning, and organizing user data using SQL
  • Performing Predictive Analytics/Modeling (i.e., Decision Trees, Neural Networks, Clustering, Classification) using Python and/or R
  • Serving as a key technical advisor to more junior team members, and working closely with the Data Engineering and Data Science teams
  • Building dashboards/reports using Tableau and delivering insights to senior management

YOUR SKILLS & EXPERIENCE:

  • Extensive, progressive commercial experience in an online gaming capacity
  • Proven experience directly building, managing, and retaining an Analytics team
  • Proficiency in collecting, cleaning, and organizing consumer data using SQL
  • Strong Predictive Modeling experience using Python and/or R
  • Progressive data visualization, dashboarding, and reporting experience using Tableau
  • Strong verbal/written communication & presentation skills across the business
  • Exceptional leadership & collaboration skills with frequent experience working cross-functionally
  • Strong passion for online gaming as well as its systems and products alike
  • Bachelor's degree in Computer Science, Economics, Mathematics, Statistics, or related field; Master's preferred

BENEFITS:

As Senior Manager, Gameplay Analytics, you can expect to make up to a $185,000 base (depending on experience).

HOW TO APPLY:

Please register your interest by sending your resume to George Little via the apply link on this page.

KEYWORDS:

Advanced Analytics, Python, R, SQL, Tableau, Data Visualization, Gaming, Online Gaming, Predictive Analytics, Insights, Predictive Modeling, Decision Trees, Neural Networks, Clustering, Regression, Personalization, User Behavior, Classification, User Data, Consumer Data, Dashboards, Reporting, Video Games, Gameplay Analytics



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00004/GL
New York
Negotiable
  1. Permanent
  2. Statistical Analyst

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Harnham blog & news

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

Weekly News Digest: 1st - 5th March 2021

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Why You Should Always Be Learning In Data Science: Tips From Kevin Tran

Last month we sat down with Kevin Tran, a Senior Data Scientist at Stanford University, to chat about Data Science trends, improvements in the industry, and his top tips for success in the market.  As one of LinkedIn’s Top Voices of 2019 within Data & Analytics. his thoughts on the industry regularly garner hundreds of responses, with debates and discussions bubbling up in the comments from colleagues eager to offer their input.  This online reputation has allowed him to make a name for himself, building out his own little corner of the internet with his expertise. But for Tran, it’s never been about popularity. “It’s not about the numbers,” he says without hesitation. “I don’t care about posting things just to see the number of likes go up.” His goal is always connection, to speak with others and learn from them while teaching from his own background. He’s got plenty of stories from his own experiences. For him, sharing is a powerful way to lead others down a path he himself is still discovering.  When asked about the most important lesson he’s learned in the industry, he says it all boils down to staying open to new ideas.  “You have to continue to learn, and you have to learn how to learn. If you stop learning, you’ll become obsolete pretty soon, particularly in Data Science. These technologies are evolving every day. Syntax changes, model frameworks change, and you have to constantly keep yourself updated.”  He believes that one of the best ways to do that is through open discussion. His process is to share in order to help others. When he has a realisation, he wants to set it in front of others to pass along what he’s learned; he wants to see how others react to the same problem, if they agree or see a different angle. It’s vital to consider what you needed to know at that stage. Additionally, this exchange of ideas allows Tran to learn from how others tackle the same problems, as well as get a glimpse into other challenges he may have not yet encountered.  “When I mentor people, I’m still learning, myself,” Tran confesses. “There’s so much out there to learn, you can’t know it all. Data Science is so broad." At the end of the day, it all comes down to helping each other and bringing humanity back to the forefront. In fact, this was his biggest advice for both how to improve the industry and how to succeed in it. It’s a point he comes back to with some regularity in his writing. “It doesn’t matter how smart you are, stay humble and respect everyone,” one post reads. “Everyone can teach you something you don’t know.” Treating people well, understanding their needs, and consciously working to see them as people instead of numbers or titles—this, Tran argues, is how you succeed in the business. To learn and grow, you must work with people, especially people with different skills and mindsets. Navigating your career is not all technical, even in the world of Data. “The thing that cannot be automated is having a heart,” he tells me sagely. Beyond this, Tran stresses the need for a solid foundation. The one thing you can’t afford to do is take shortcuts. You have to learn the practicalities and how to apply them, but to be strong in theory as well.  Understanding what is happening underneath the code will keep you moving forward. He compares knowing the tools to learning math with a calculator. “If you take the calculator away, you still need to be able to do the work. You need the underlying skills too, so that when you’re in a situation without the calculator, you can still provide solutions.” By constantly striving to collaborate and improve, Tran believes the Data industry has the best chance of innovating successfully.  If you’re looking for a new challenge in an innovative and collaborative environment, we may have a role for you. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more. 

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