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Director Product & Advanced Analytics

New York
US$190000 - US$225000 per year
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Director Product & Advanced Analytics
Media Streaming
New York or remote on EST
$190,000 - $225,000

Are you obsessed with how we can use data to personalize customer experiences and enhance loyalty? Do you like to innovate new methodologies and combine highly advanced analytics techniques with product insights to develop products that we don't know we need until we have them? If you are a hands-on team manager with a highly statistical background in SQL, R and Python, and have been a hands-on statistical modeler in your career then I have a great opportunity for you to join one the leading analytics teams in the US.

THE COMPANY:

This globally renowned media streaming company are cutting edge in every way. From disrupting the market to bring us new personalized products and services that we didn't even know we needed, to combining user research and data science techniques to ensure that we stay consistently engaged for multimedia streaming, this household name and a force to be reckoned with!

THE ROLE - Director Product & Advanced Analytics

As a Director Product & Advanced Analytics, you will be leading a multidisciplinary and highly technical team of Data Scientists, Product Analysts and User Researchers who are all technically strong in SQL, Python and R, building highly sophisticated statistical models to answer key business questions about how to personalize all products and services to ensure customer loyalty and product usage growth. You will:

  • Set the strategic vision of the Data Science, User Research and Product Analytics teams, prioritizing projects and ensuring that customer personalization is at the forefront of all data-driven decisions made
  • Be a coach and player, hands on when needed in this innovation and product development role using data to predict the success of products and services that haven't been created yet, forecasting their growth and usage using SQL, Python and R, and building time series, linear and logistic regression and decision tree models, as well as delivering insights and recommendations
  • Work with a broad range of hard-to-capture data sets across both online and offline channels to understand customer behaviors, needs, wants and attitudes, turning these into insightful stories that can be used by the product teams to create new personalized products for the individual user
  • Manage, develop and enhance the skills of your team, which although starting at 6-8 people will likely double in size within the first 12 months.

YOUR SKILLS AND EXPERIENCE:

  • Degree educated in Psychology, Math, Statistics, Operational Research or similar numerical discipline, with a PhD preferred but not essential
  • Strong technical skills in SQL, Python and R with the ability to build highly sophisticated models such as time series, regression, decision trees, random forests, xgboost etc
  • Exceptional communicator, with proven capabilities in demonstrating your ability to turn highly complex analyses into stories and customer journeys that can be used by multiple technical and non-technical audiences
  • Background in Product Analytics within an eCommerce environment is highly desirable, with the ability to apply complex human behaviors and attitudes to enhance the development of new products or services

BENEFITS:

As a Director Product & Advanced Analytics you can expect to earn up to $225,000 + benefits (depending on your experience)

HOW TO APPLY:

Please register your interest by sending your resume to Jenni Kavanagh via the Apply link on this page

KEYWORDS:

Product Analytics, SQL, Python, R, Analytics, Strategy, Data Science, Product, User Research, Advanced Analytics, Foundational Research, Business, Time-Series, Regression, Statistical Analysis, Predictive Analytics, Model, Modell, Modeling, Modelling, Senior, Manage, Manager, Stakeholder Manager, Customer Acquisition, Looker, Retention, Sales, Growth, Advanced Analytics, Product, Tableau, AWS, Scala, Media, Streaming, Quant Research, Qual Research, Customer Behavior

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110037/JK
New York
US$190000 - US$225000 per year
  1. Permanent
  2. Statistical Analyst

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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: 5th - 9th April 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.    The Drum: How data visualisation turns marketing metrics into business intelligence Gathering data is just one part of a marketer’s job but having the ability to turn this data into something visually stunning, informative and easy to use is another skill completely.  Marketers, on the whole, are extremely visual learners along with around 65 per cent of the population. Most of us are able to absorb data more effectively if the information being presented to us is done in such a way that is pleasing to the eye. And this is why Data Visualisation exists; it allows us to group, organise and represent data sets in a way that allows us to analyse larger quantities of information, compare findings, spot patterns and extract meaningful insights from raw data. Not only does Data Visualisation allow us to learn more effectively, but we can then turn this understanding into much broader and deeper Business Intelligence.  To read more on the positives of Data Visualisation and how to translate this into meaningful Business Intelligence, click here.  ZDNet: The five Vs of customer data platforms According to ZDNet, Customer Data Platforms (CDPs) are the hottest marketing technology today, offering companies a way to capture, unify, activate, and analyse customer data. Research done in 2020 by Salesforce showed that CDPs were among the highest priority investments for CMOs in 2021. If you’re planning to invest in a CDP this year, what five critical things do you need to think about when developing a successful strategy? ZDNet tells all.  Velocity - Your systems need to manage a high volume of data, coming in at various speeds.Variety - Every system has a slightly different main identifier or "source of truth," and the goal is to have one. This starts with being able to provision a universal information model, or schema, which can organize all of the differently labelled data into a common taxonomy. Veracity - Companies must ensure they can provision a single, persistent profile for every customer or account.Volume - It has been theorized that, in 2020, 1.7MB of data was created every second for every person on Earth. If you want to use those interactions to form the basis of your digital engagement strategy, you have to store them somewhere. Value - Once you have a clean, unified set of scaled data – now’s the time to think about how to derive value from it.  To learn more, read the full article here. Towards Data Science: How to Prepare for Business Case Interview Questions as a Data Scientist When you think of Data Science, the first thing that comes to mind will be technical knowledge of coding languages and fantastic statistical ability; softer skills such as communication and exceptional business knowledge may be overlooked. However, this is where many budding Data Scientists trip up. It is these softer skills and business acumen that sets brilliant candidates apart from others.  But how, when not usually taught at university, do you gather the business knowledge that will set you apart from the competition and showcase it in interview? Towards Data Science shares a few key pointers. Build a foundation – Brush up on your business basics. Research project management methodologies, organisational roles, tools, tech and metrics - all are crucial here. Company specifics – Research your company and its staff. Make sure your knowledge is tailored to the company you’re interviewing for. Products – This is where you’ll stand out above the rest if you get it right. The more you can know the ins and outs of products and metrics at the company, the more prepared you will be to answer business case questions. Read the full article here.  Harnham: Amped up Analytics: Google Analytics 4 Joshua Poore, one of our Senior Managers based in the US West division of Harnham, explores Google’s new and improved data insight capabilities, predominantly across consumer behaviours and preferences.  This exciting new feature of Google was born in the last quarter of 2020 and has now fully come into its infancy, and it’s an exciting time for Data & Analytics specialists across the globe. Joshua explores four key advantages of Google Analytics 4.0. Combined data and reporting - Rather than focusing on one property (web or app) at a time, this platform allows marketers to track a customer’s journey more holistically. A focus on anonymised data - By crafting a unified user journey centred around machine learning to fill in any gaps, marketers and businesses have a way to get the information they need without diving into personal data issues.Predictive metrics - Using Machine Learning to predict future transactions is a game changer for the platform. These predictive metrics for e-commerce sites on Google properties allow for targeted ads to visitors who seem most likely to make a purchase within one week of visiting the site. Machine Learning driven insights - GA4 explains it “has machine learning at its core to automatically surface helpful insights and gives you a complete understanding of your customers across devices and platforms.” Machine Learning-driven insights include details that elude human analysts.  To read Joshua’s full insights on GA4, click here.  We've loved seeing all the news from Data & 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.   

Daniel Lewis

Daniel Lewis

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

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