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Assistant Manager of Data Science

New York
US$140000 - US$150000 per annum

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Assistant Manager of Data Science
CPG
New York Metropolitan Area
$140,000-$150,000

Do you want to work for a cutting-edge company and be surrounded by an expert level team? If you are an Advanced Analytics expert with experience working in the Consumer Goods industry then this is the perfect role for you!

THE COMPANY:

This world-renowned CPG business has already put so much focus into their analytics teams, so much so that they named it the Analytics Center of Excellence. But now, they want to expand and improve even further in order to fully optimize and utilize their data to the best of their ability. They are looking to bring on senior analytics professionals like you to focus on marketing analytics and customer data in order to bring insights to the team!

THE ROLE:

Under the direction of the Lead Data Scientist and directly reporting to the Director of Data Science and Analytics, you will...

  • Work as an individual contributor to convert consumer insights into actionable solutions!
  • Study media audiences to derive analysis of customer behavior and test the impact of content on the audiences.
  • Using Python/R and SQL, you will develop attribution models such as Random, propensity, market basket analysis, and regression. You will also do A/B testing.
  • Assist in leading the team in using machine learning algorithms to identify irregularities in the consumer/retailer data and help upsell the products.
  • Communicate with high-level stakeholders in order to influence successful decisions.

SKILLS AND REQUIREMENTS:

  • Masters in an Analytics or STEM-related field
  • Proficient with Python/R, SQL, and Google Analytics
  • Experience working at a CPG company
  • Background working with audience modeling and advertising technologies
  • Excellent communication skills in order to present information to business stakeholders

SALARY & BENEFITS:

As an Associate Manager of Data Science, you can expect to earn up to $150,000 (depending on experience) + an excellent benefits package!

HOW TO APPLY:

Please register your interest by sending your resume to Chinue Ellis via the Apply link on this page.

KEYWORDS:

SQL, R, Python, Predictive Modelling, Regression, Statistics, Google Analytics, Excel, Marketing, Analysis, Customer Insight, Digital, eCommerce, Retail, Stakeholder Management, Strategy, ROI, Campaigns, Direct Marketing, Online, Tableau, Optimization, Segmentation, Modeling, Advanced Analytics, Machine Learning, Recommendation Models, CPG

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101282/ce7
New York
US$140000 - US$150000 per annum
  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: 1st - 5th March 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.  Analytics Insight: Top 10 analytics and business intelligence buzzwords in 2021 If you are a fan of both buzzwords and analytics, then look no further, this article from Analytics Insight is for you! The team at the global publication identify and explore the top buzzwords that are being used to define business intelligence and analytics techniques across the industry in 2021. A few of these include: Predictive AnalyticsEmbedded AnalyticsCognitive ComputingData ScienceX Analytics Ultimately, there are a whole host of buzzwords and key terms being used in Data & Analytics at the moment, but professionals should keep up to date with the core (and most influential) technologies and insights in their area of expertise. Find out more about the top 10 buzzwords and view their definitions here. Forbes: Diversity is what you see, Inclusion is what you do Writing for Forbes, Paolo Gaudiano discusses how to really examine the values and culture of an organisation: you need to change the way in which you think about – or approach – understanding the unique contributions of your team. “Being forced to think about recreating an organization from the inside out, i.e., by actually thinking from the point of view of the individual employees and their experiences, helped us to clarify how we can think about—and define—diversity and inclusion.” It is in considering diversity and inclusion in two separate approaches, that an organisation can truly make this a core area of focus. Afterall, Gaudiano highlights that, “Diversity is a measure of how an individual’s personal characteristics differ from those of the normative majority of an organisation; inclusion is the act of ensuring that people’s experiences within an organisation are not impacted negatively as a result of their personal characteristics.” We need to provide more support, education and tools to ensure that our companies can sustain a growing level of diversity, and to enjoy an inclusive environment. Read more on this here. Computer Weekly: It’s now or never for UK fintech, government told The contributors at Computer Weekly have this week reported on how a Treasury-commissioned review of the UK’s future in financial technology (fintech) has told the government that it must urgently introduce effective policies in five key areas if the fintech industry is to continue to thrive. Policy & Regulation To include creating a new regulatory framework for emerging technology.Skills To include retraining and upskilling adults in support of UK fintech.Investment To include introducing a global family of fintech indices.International To include driving international collaboration and delivering an international action plan for fintech.National Connectivity To include accelerating the development and growth of fintech clusters. The review was comprehensive and provides a startling call to action for senior government officials. Read more on the future growth of the UK’s fintech sector here.  AdAge: First-party data strategies for advertisers and publishers in the age of privacy Can brands partnering with publishers discover better Consumer Insights? That’s the question that this insight from AdAge explores, as brands consider shifting their marketing strategies to align with privacy regulations (and maintain or regain consumer trust). Some of the ways brands are responding are by looking at: First-party Data Strategies Marketers need to pinpoint the right customers to target for different messages. One way to do this is by partnering with publishers and other companies that can offer granular consumer insights built from first-party data in a privacy-safe way.Direct Relationships With Publishers By creating ties with publishers, through trusted networks or direct relationships, brands will be operating in a premium environment, thanks to the data and insights the publishers can provide.Creating A New Digital World Marketing’s priorities now need to shift to first-party data strategies and building trusted networks of first-party data owners. This gives brands an opportunity to not only gain more control over their advertising but also to rebuild consumer trust in advertising. To find out more about how brands and marketers are working together in a digital world, take a look at the article in full 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.

Sam Maughan

Sam Maughan

05. March 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

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