Manager Product Analytics

Boston, Massachusetts
US$110000 - US$145000 per year

Manager, Product Analytics
eCommerce Retail
Greater Boston Area
$110,000 - $145,000

Are you obsessed with how we can use data to optimize customer experiences and improve business products? Do you like to innovate new methodologies and combine highly advanced analytics techniques with rich data to develop products and services that are more efficient, effective? If you are a hands-on Product Analytics specialist, with team management skills and a highly statistical background in SQL, R and Python, and can optimize product performance then I have a great opportunity for you to join one the leading analytics teams in the US.

THE COMPANY:

This globally renowned eCommerce Retail 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 advanced methodologies and data science techniques to ensure that we stay consistently buying more products, this household name and a force to be reckoned with!

THE ROLE -Manager, Product Analytics:

As a Manager, Product Analytics, you will be a leading member of a multidisciplinary and highly technical team of Data Scientists, Web Analysts and Product Analysts who are all technically strong in SQL, Python and R, building highly sophisticated solutions to answer key business logistics questions about how to optimize product features (both hardware and software, and the path through the website, to ensure customer loyalty and product upsell/cross sell growth. You will:

  • Set the strategic vision of the product initiatives, prioritizing projects and ensuring that customer satisfaction and advanced methodologies are at the forefront of all data-driven decisions made, to provide first-class solutions to optimize features, integrations and operations
  • Be a coach and player, hands on in this innovation team, where you will be focusing on creating new methodologies using customer-rich product data to design solutions that are efficient and effective, using SQL, Python and R, making both the business operations and customer engagement better for all involved
  • Work with a broad range of product, operations and web data sets across both online and offline channels to understand areas for improvement for speed and efficiency, turning these into insightful stories that can be used by the product, marketing and customer experience teams to optimize across all areas of the business

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 that can be used by multiple technical and non-technical audiences
  • Background within an eCommerce or retail environment is highly desirable, with the ability to apply complex product analytics methodologies to enhance the development of new products or services that optimize business operations
  • Web Analytics tools such as Google Analytics, Adobe and Omniture desirable but not essential

BENEFITS:

As a Manager, Product Analytics you can expect to earn up to $145,000 + benefits, including equity (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, SQL, Python, R, Analytics, Strategy, Data Science, Product, Retail, eCommerce Advanced Analytics, 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, Customer Behavior, Google Analytics, SiteCatalyst, Omniture

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69114/JK
Boston, Massachusetts
US$110000 - US$145000 per year
  1. Permanent
  2. Statistical Analyst

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‘Tis The Season Of Data: Black Friday Is Here

‘Tis The Season Of Data: Black Friday Is Here

It’s that time of year again. Decorations are going up, the temperature is dropping daily, and the year’s biggest shopping weekend is upon us.  Black Friday and Cyber Monday may have started stateside, but they’re now a global phenomenon. This year, in the UK alone, shoppers are expended to spend £8.57 billion over the four-day weekend. But, for retailers, this mega-event means more than a cash injection. In the world of Data, insights gained from shopping and spending habits during this period can dictate their product and pricing strategies for the next twelve months.  So what is it, exactly, that we can stand to learn from the Black Friday weekend? THE GHOST OF BLACK FRIDAY PAST There are a few interesting takeaways from 2018’s Black Friday weekend that will likely impact what we see this year.  Firstly, and perhaps unsurprisingly given that it’s a few years since the event has become omnipresent, spending only increased about half as much as initially predicted. There are a number of reasons for this, but cynicism plays a central role. More and more, consumers are viewing Black Friday deals with an element of suspicion and questioning whether the discounts are as good as they’re promoted to be. This, combined with other major annual retail events, such as Amazon’s Prime Day, means that this weekend no longer has the clout it once did.  However, 2018 also saw marketers doing more to stand out against the competition. Many businesses have moved away from traditional in-your-face sales messaging and some are even limiting their Black Friday deals to subscribers and members. By taking this approach, their sales stand out from the mass market and can help maintain a level of exclusivity that could be jeopardised by excessive discounts. In addition to branding, marketers making the most of retargeting saw an even greater uplift in sale. Particularly when it came to the use of apps, those in the UK using retargeting saw a 50% larger revenue uplift than those who didn’t.  So, having reviewed last year’s Data; what should businesses be doing this year in order to stand out? GETTING BLACK FRIDAY-READY WITH DATA Businesses preparing for Black Friday need to take into account a number of considerations involving both Marketing and Pricing. For the latter, Data and Predictive Analytics play a huge role in determining what items should go on sale, and what their price should be.  Far from just being based on gut instinct or word-of-mouth, algorithms derived from Advanced Analytics inform Machine Learning models that determine what should be on sale, and for how much. These take into account not only how many of each discounted product need to be sold to produce the right ROI, but also what prices and sales should be for the rest of the year in order to make the sale financially viable.  In terms of Marketing, Deep Learning techniques can be used to accurately predict Customer Behaviour and purchases. These predictions can then reveal which customers are likely to spend the most over the weekend, and which are likely to make minimal purchases. Marketers can then, in the lead up to Black Friday, target relevant messaging to each audience whether it be “get all you Christmas shopping in our sale” or “treat yourself to a one-off item”. By carefully analysing the Data they have available and reviewing the successes and failures of their Black Friday events, businesses can generate greater customer loyalty and improve their sales year-round. If you’re looking to build out your Marketing Analytics team or take the next step in your career, we can help. Take a look at our latest opportunities or get in touch with one of our expert consultants to find out more. 

The Harnham 2019 Data & Analytics Salary Guide Is Here

We are thrilled to announce the launch of our 2019 UK, US and European Salary Guides. With over 3,000 respondents globally, this year’s guides are our largest and most insightful yet.  Looking at your responses, it is overwhelmingly clear that the Data & Analytics industry is continuing to thrive. This has led to an incredibly active market with 77% of respondents in the UK and Europe, and 72% in the US, willing to leave their role for the right opportunity.  Salary expectations remain high, although we’re seeing that candidates often expect 2-10% more than they actually achieve when moving between roles.  Globally, we’ve also seen a change in the reasons people give for leaving a position, with a lack of career progression overtaking an uncompetitive salary as the main reason for seeking a change.   There also remains plenty of room for industry improvement when looking at gender parity; the UK market is only 25% female and this falls to 23% in the US and 21% across the rest of Europe.  In addition to our findings, the guides also include insights into a variety of markets and recommendations for both those hiring, and those seeking a new role.  You can download your copies of the UK, US and European guides here.

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