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Director Data Science
$230,000 - $250,000 + bonus + equity
Are you obsessed with how we can use data to personalize customer experiences and predict behaviors? Do you like to innovate new methodologies and combine highly advanced analytics techniques with customer-rich data to develop products and services that increase spend and brand loyalty? If you are an experienced Data Science and Customer Analytics leader with a highly statistical background in SQL, R and Python, and can build statistical models to predict customer behaviors then I have a great opportunity for you to join one the leading analytics teams in the US.
A globally renowned online marketplace in the Greater Boston Area that has millions of rows of rich customer engagement data, are looking for an experienced Data Science leader to come on board to build out their marketing effectiveness and predictive models, delivering insights into who their customers are, how they engage with the brand and creating targeted and efficient communications strategies that will increase new customer acquisition, and reduce retention across all channels.
THE ROLE - Director, Data Science
As a Director, Data Science, you will be the leader of a multidisciplinary and highly technical team of Data Scientists 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 upsell/cross sell growth. You will:
YOUR SKILLS AND EXPERIENCE:
As a Director, Data Science you can expect to earn up to $250,000 + 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
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, Director, Director of Data Science, Stakeholder Manager, Customer Acquisition, Looker, Retention, Sales, Growth, Advanced Analytics, Product, Tableau, AWS, Scala, Customer Behavior
US$145000 - US$155000 per annum
Do you have a background leading an Analytics or Data Science team at an eCommerce company and have a strong understanding of machine learning?
Do you have strong predictive modeling skills using Python or R and have a background working at either media or tech companies?
US$120000 - US$140000 per annum
Do you have proven experience managing an analytics team and have strong predictive modeling skills using Python or R?
£50000 - £65000 per annum
Milton Keynes, Buckinghamshire
This organisation operates within the finance and accountancy sector, offering its customers a community as well as the chance to grow, develop, and upskill.
With over 10 years experience working solely in the Data & Analytics sector our consultants are able to offer detailed insights into the industry.
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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 firstname.lastname@example.org.
26. February 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. KDnuggets: 10 resources for data science self-study If you are interested in getting into data science, there are two basic pathways that you can opt for. There’s the traditional college degree route or the self-study option, the latter of which is growing in popularity among aspiring data scientists. This informative article from KDnuggets provides some insightful tips for data science self-study, grouped into three main categories: Resources for building fundamental knowledge; resources for data science practice; and resources for networking and continuous studies. Resources for building fundamental knowledge:Massive Open Online Courses (MOOCs)Learning from a TextbookYouTubeKhan AcademyResources for Data Science practice:KaggleInternshipsResources for networking and continuous studies:MediumLinkedInKDnuggetsGitHub Find out more here. Analytics India Magazine: How machine learning streamlines risk management Abhaya K Srivastava, SVP at Northern Trust Corporation, recently spoke at the Machine Learning Developers Summit 2021. Srivastava delved into how different sectors including financial, healthcare and retail are making use of emerging technologies like AI and Machine Learning. One of the main takeaways from the speaker session was discussions around how Machine Learning can support how organisations streamline their Risk Management. Srivastava stated, “It is essential for us to establish the rigorous governance processes and policies that can quickly identify when the model begins to fail.” He continued, “The terms of AI are not new, but businesses and organisations have started using these technologies in a different way. We have noticed the influence of machine learning in business applications, ML is playing an important role in Risk Management and there has been a constant focus on how risks are being detected, reported, managed.” There are a range of different machine learning techniques that can be applied to support risk management. It is the role of organisations, and their partners to discover how these processes can be applied. Read more on this here. Information Week: 3 Ways to Empower Female Software Engineers on Your Team We think this is a great article from Information Week that acknowledges the importance of establishing greater diversity and inclusion within software engineering, in particular to empower women in the industry. The article focuses on three areas: Create an inclusive team:Building an inclusive team is a strategic process and should include making sure everyone has a voice and that the workplace is a safe place to take risks.Provide a support system:Support establishes trust and shows a commitment to the well-being of your people. When leaders support their employees, it can significantly affect job satisfaction and performance.Enable women to inspire othersThe first thing to do is make sure the women in your organisation have a seat at the table; they should have a say in the decision-making process. Even if you have a good understanding of these, it’s important to keep educating yourself and the wider team in order to implements processes and strategies that make for a truly inclusive team. Read more on this here. TechRepublic: 8 must-read leadership books recommended by tech titans and innovators Are you looking for your next read to help you elevate your visibility and skill as a leader in the tech industry? Look no further, as TechRepublic have put together a list of leadership books recommended by notable leaders from within the industry. Here are a few: The Ride of a Lifetime (Robert Iger) - Recommended by Bill GatesDrop the Ball (Tiffany Dufu) - Recommended by Sheryl SandbergMindset (Dr Carol S. Dweck) - Recommended by Satya NadellsTrailblazer (Marc Benioff) - Recommended by Susan Wojcicki It’s valuable to have insight from leaders that are already leading the way for tech innovation in their field, inspiring and supporting future leaders to achieve great things too. Click here to read the full list of recommended leadership books from Bill Gates, Satya Nadella, Sheryl Sandberg, Tim Cook, and other notable industry leaders. 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 email@example.com.
19. February 2021