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Senior Manager, Advanced Analytics

New York
US$145000 - US$155000 per annum
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Senior Manager, Advanced Analytics
Internet
New York
$145,000 - $155,000 + Benefits + Bonus

Are you passionate about joining a transformational company that actively helps hundreds of thousands of families annually? A leading tech company is looking for an experienced Senior Manager, Advanced Analytics to handle the successful customer analysis and A/B testing to meet business growth in New York City.

THE ROLE:

As Senior Manager, Advanced Analytics, you will be the Advanced Analytics Lead for capturing data, analyzing results, and delivering actionable insights to a variety of key stakeholders. You will be responsible for:

  • Enabling Product and Marketing strategy development through data analytics and actionable recommendations
  • Acting as Key Technical Advisor on analytics across tools such as Python, R, SQL, Google Analytics, and Tableau
  • Proposing, implementing, and analyzing A/B tests to optimize funnel conversion and program performance
  • Owning an end-to-end analysis to identify key drivers of emerging trends and recommending actions to several stakeholders across the business

YOUR SKILLS & EXPERIENCE:

  • You must have progressive commercial web analytics experience in eCommerce
  • Strong technical skills in advanced analytical tools (e.g., Python, R, SQL, & Tableau)
  • Proven proficiency in web analytics platforms (e.g., Google Analytics, Adobe Analytics)
  • Proven experience building up, coaching, and managing analytics teams
  • Deep understanding of digital product/digital marketing & combining disparate datasets
  • Experience managing a diverse set of stakeholders and acting as an internal stakeholder
  • Strong written/verbal communication and presentation skills
  • Bachelor's degree in Mathematics, Statistics, Economics, Business, Marketing, or related field; Master's preferred

BENEFITS:

As Senior Manager, Advanced Analytics, you can expect to make up to $155,000 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, Google Analytics, Customer Data, SQL, Python, R, Tableau, Data Visualization, A/B Testing, Insights, Adobe Analytics, Data Science, Statistical Modeling, Predictive Modeling, Cluster Analysis, Regression, Decision Trees, Audience Modeling, Propensity Modeling, Google Tag Manager

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00007/GL
New York
US$145000 - US$155000 per annum
  1. Permanent
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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.

Weekly News Digest: 22nd - 26th Feb 2021

This is Harnham’s weekly news digest, the place to come for a quick breakdown of the week’s top news stories from the world of Data & Analytics.  Search Engine Journal: 4 ways call tracking is changing (and why it’s a good thing) Call tracking is no longer about a customer seeing an ad, calling up the company, telling them how much they loved the ad and then deciding to purchase goods. This is a positive thing really because it wasn’t the most effective way for businesses to track how well adverts were doing anyway - who really remembers where they saw a billboard that took their interest, or what time of day an advert popped up on the TV? As call tracking technology becomes more advanced, call analytics have become much more accessible for all. Not only have they been able to transform how businesses of all shape and size advertise and track their success, but also how they market to potential audiences and track their sentiment.  This article from Search Engine Journal looks at the evolution of call tracking and call analytics from its most basic form, how it works now and what the future of this crucial set of analytics will look like in the future.  Read more on this here.  Towards Data Science: Data Science Year Zero Skills or qualifications in Data Science are becoming incredibly sought after by many employers, but the knowledge of how to break into the sector is still a little unclear for potential candidates. In this article by Towards Data Science, they break down the crucial elements of how to successfully enter the industry in four easy steps.  What the author, Bala Vishal, lacked when he started and how you can set off on a better footing.The most important skills and tools to have under your belt.Which skills should you home in on first.How to thrive in the workplace. This incredibly insightful piece should be a ‘must-read’ for any budding Data Scientist looking to break into Data in 2021 and beyond.  Read more here.  KD Nuggets: 10 Statistical Concepts You Should Know for Data Science Interviews This article is perfect for anyone in the Data Science industry. Whether you’re new to the game or looking to take the next step on the career ladder, make sure you brush up on these crucial statistical concepts you should know inside out before entering interview.  A few, in no order, include: Z tests vs T tests An invaluable piece of knowledge that will be used daily if you are involved in any statistical work.Sampling techniques Make sure you’ve got the main five solidified in your knowledge bank - Simple Random, Systematic, Convenience, Cluster, and Stratified sampling.Bayes Theorem/Conditional Probability One of the most popular machine learning algorithms, a must-know in this new era of technology.  Want to know about the other seven? Read more here. Forbes: 48 per cent of Sales Leaders Say Their CRM System Doesn’t Meet Their Needs. The Good News Is That This Is Fixable. This article by Gene Marks explores why teams aren’t happy with their current CRM systems, and how this can be remedied. New research from SugarCRM found: 52 per cent of sales leaders reported that their CRM platform is costing potential revenue opportunities.50 per cent of the companies said they cannot access customer data across marketing, sales and service systems.Nearly one-third complained that their customer data is incomplete, out of date, or inaccurate. While damning statistics, Marks then goes into how this worrying situation can be fixed for good. He says: “Like just about all problems in business, this problem comes down to two factors: time and money. The blunt fact is that most companies are not willing to spend the necessary time or money needed to enable their CRM systems to truly do what they’re designed to do. CRM systems are not just for sales teams. And they're not just for service teams. For a CRM system to be effective, a company must adapt it as its main, collaborative platform.” Read more on this here. We've loved seeing all the news from Data and Analytics in the past week, it’s a market full of exciting and dynamic opportunities. To learn more about our work in this space, get in touch with us at info@harnham.com.

Ross Whatling

Ross Whatling

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

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