Director Data Science (Marketing)

New York
US$150000 - US$170000 per annum + Bonus + Pension + 401K

Director Data Science (Marketing)
Insurance
New York City
$150,000-$170,000

I am currently partnered with one of the most popular names in the insurance industry! They are urgently looking for someone to come on board at the Director level who is subject matter expert within advanced analytics with a marketing focus! If this describes you, please keep reading!

THE COMPANY:

My client is one of America's largest insurance companies and have created a Center of Excellence within analytics and have vast internal and external database that make them one of the most data rich insurance brands in the country.

THE ROLE:

The ideal candidate has a proven expertise within advanced analytics with a marketing focus. In this role, you will be comfortable switching on and off from hands on modeling to translating technical insights into actionable initiatives that will guide segmentation and optimization of both online and offline channels. You will be:

  • An expert with market mix modeling, multi-touch attribution, online and offline channel optimization, campaign performance strategy and A/B testing (both hands on as well as leading the technical team building out these technical insights).
  • An expert with advanced predictive and statistical modeling: linear and logistic regression, decision trees, random forest, classification, clustering, etc.
  • Able to bridge the gap between technical hands on analysis and creating strategic data stories that will captivate stakeholders.

YOUR SKILLS AND EXPERIENCE:

  • Degree educated in a STEM subject.
  • Expert proficiency in tools like and in SQL, Python and R for predictive and statistical modeling.
  • Experienced with channel strategy, market mix modeling, campaign performance evaluation, multi-touch attribution, predictive modeling and A/B testing.
  • Insurance/and or banking experience preferred.

THE BENEFITS:

  • $150,000-170,000 Salary

HOW TO APPLY:

Please register your interest by sending your CV to Sasha Baez via the Apply link on this page.

KEYWORDS:

Insurance, Director of Data Science, marketing, data driven, SAS, SQL, R, Python, client facing, A/B testing, natural, channel strategy, market mix modeling, campaign performance, optimization, customer LTV, campaign performance evaluation, multi-touch attribution, channel, linear regression, logistic regression, decision trees, random forest, classification

Send similar jobs by email
600/Sb
New York
US$150000 - US$170000 per annum + Bonus + Pension + 401K
  1. Permanent
  2. Statistical Analyst

Similar Jobs

Salary

US$150000 - US$170000 per year

Location

New York

Description

Do you understand why customers buy what they buy and what motivates them to spend their money?

Salary

US$130000 - US$145000 per annum

Location

New York

Description

A top information tech brand is looking for a hands on data scientist with in depth background in analyzing healthcare and medical data!

Salary

£50000 - £60000 per annum + Benefits

Location

North London, London

Description

This is a great opportunity for a data scientist to join a leading global sports start up and further their career in a reputable analytics team

Salary

US$120000 - US$140000 per annum

Location

New York

Description

Are you a predictive analytics wizard that can build models to better understand consumer behavior? Python expertise is a must!

Salary

US$175000 - US$200000 per year

Location

New York

Description

Can you combine cognitive behaviors with new products to service the market? If you are statistically savvy then this could be a great next step

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.

‘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.

Recently Viewed jobs