Harnham
SEARCH
Shortlist

Manager, Advanced Omnichannel Analytics

New York
Negotiable
Apply Save job

Manager, Advanced Omnichannel Analytics
eCommerce
Greater New York Metropolitan Area
$140,000 - $160,000

A leading CPG global enterprise is looking for an experienced Manager, Advanced Omnichannel Analytics to lead the successful predictive modeling and omnichannel analytics to meet business growth in the Greater New York Metropolitan area.

THE ROLE:

As Manager, Advanced Omnichannel Analytics, you will work closely with the Head of Advanced Analytics in analyzing large amounts of historical data, detecting patterns, and building machine learning models to enhance the enterprise's predictive and prescriptive capabilities. You will be responsible for:

  • Gathering syndicated data, analyzing it, and then building predictive models using Python or R
  • Leveraging AI & ML to forecast omnichannel business for investment & product supply decisions
  • Operating BI omnichannel roadmap to enable senior management & incremental sales
  • Serving as a technical advisor on key global projects to various stakeholders across the business

YOUR SKILLS & EXPERIENCE:

  • Progressive experience in Advanced Analytics, Data Science, Machine Learning, & Artificial Intelligence
  • Proven experience working directly in a major retailer capacity
  • Exceptional project management and stakeholder engagement skills
  • Proven hands-on experience building predictive models in Python, R, or SQL
  • Strong technical skills using ThoughtSpot or similar query-based BI program
  • Strong understanding of omnichannel analytics and machine learning
  • Proven experience working with large amounts of syndicated data (IRI, Nielsen, NPD, etc.)
  • Proven experience building roadmaps, forecasting sales, and performing ROI analysis
  • Strong written/verbal communication and presentation skills across the business
  • Extensive experience working with sales, business intelligence, and shopper research
  • Bachelor's degree in Computer Science, Mathematics, Statistics, or related field; Master's preferred

BENEFITS:

As Manager, Advanced Omnichannel Analytics, you can make up to a $160,000 base (depending on your experience).

HOW TO APPLY:

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

KEYWORDS:

Omnichannel, Data Science, Machine Learning (ML), Artificial Intelligence (AI), Advanced Analytics, Predictive Analytics, Python, R, SQL, ThoughtSpot, Business Analytics, Tableau, PowerBI, IRI, Syndicated Data, Road Mapping, Sales Forecasting, ROI Analysis, Prescriptive Analytics, Predictive Models, Power BI, Cluster Analysis, Churn, Regression

Apply Save job
Send similar jobs by email
00010/GL
New York
Negotiable
  1. Permanent
  2. Statistical Analyst

Similar Jobs

Senior Manager, Analytics & Data Science
Salary

US$145000 - US$155000 per annum

Location

Boston, Massachusetts

Description

Do you have a background leading an Analytics or Data Science team at an eCommerce company and have a strong understanding of machine learning?

ADD TO SHORTLIST
Senior Manager, Marketing Data Science
Salary

Negotiable

Location

New York

Description

Do you have strong predictive modeling skills using Python or R and have a background working at either media or tech companies?

ADD TO SHORTLIST
Manager, Customer Analytics
Salary

US$120000 - US$140000 per annum

Location

Boston, Massachusetts

Description

Do you have proven experience managing an analytics team and have strong predictive modeling skills using Python or R?

ADD TO SHORTLIST
Data Scientist
Salary

£50000 - £65000 per annum

Location

Milton Keynes, Buckinghamshire

Description

This organisation operates within the finance and accountancy sector, offering its customers a community as well as the chance to grow, develop, and upskill.

ADD TO SHORTLIST

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

26. February 2021

News

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. 

William Reichert

William Reichert

19. March 2020

News

Recently Viewed jobs