Principal Data Scientist

Boston, Massachusetts
US$175000 - US$190000 per year

Principal Data Scientist
eCommerce
Boston
$175,000 - $190,000

Do you want to join a rapidly growing eCommerce company who have a global presence, and specialize in customer-focused products? This company is revolutionizing the way people buy products online. As a result, they have had a huge amount of investment and are looking for a highly skilled Principal Data Scientist with a background using open source technologies, including Python, SQL and R to build sophisticated predictive and machine learning algorithms to optimize their marketing spend and achieve key business goals? If you're looking for a new challenge and have experience in the end-to-end customer/product analytics cycle, specifically in the online space, then this could be the next step for you.

THE ROLE:

As a Principal Data Scientist, you will be deemed an expert in predictive analytics, proactively involved in all aspects of leveraging advanced analytics and machine learning to grow the business, from marketing, to product to sales, performing highly statistical analysis to understand how effective each channel of communication is for the business to optimize spend and ROI. This is a senior role in the team, and you will be hands-on with team management responsibilities. You will focus on:

  • Understanding all the company's marketing, product, customer and wider business constraints across all channels of engagement and be the go-to person for leading the way in innovation of advanced approaches to predicting behaviors
  • Building and evolving existing models and algorithms to improve automation, efficiency and effectiveness across the business, especially marketing and customer engagement. Models may include Time Series, Customer Lifetime Value, Propensity and Recommendation Engines among others
  • Working with diverse teams across the business including Marketing, Sales and Engineering teams, as well as the wider Analytics team across the globe to ensure that the quality of the data and models are of the highest standard, and their business questions are answered
  • Delivering insights and recommendations to diverse stakeholders on how to improve their marketing or product performance and increase customer engagement and sales

YOUR SKILLS AND EXPERIENCE:

  • Degree educated, preferably with a Masters of PhD in a numerical discipline such as Math, Stats, Computer Science or similar
  • Experienced in building advanced models and algorithms including Recommendation Engines, Classification, Clustering, Customer Lifetime Value and Propensity models in R/Python as well as strong SQL coding background
  • Proven experience in building and maintaining relationships, as well as delivering insights and recommendations to C-Level stakeholders
  • Project management capabilities, with a strong business acumen are essential

BENEFITS:

As a Principal Data Scientist, you can expect to earn up to $190,000 (depending on experience), plus competitive benefits.

HOW TO APPLY?

Please register your interest by sending your resume to Jenni Kavanagh via the Apply link on this page

KEYWORDS:

Python, SQL, R, Market Mix Modelling, Multi-Touch Attribution, Strategy, Client facing, Recommendations, ROI, Campaigns, Forecasting, Product, Pricing, Promotion, Loyalty, Customer Engagement, Consultancy, TV, Radio, Newspaper, Social Channels, Marketing effectiveness, Marketing Efficiency, Data Science, Classification, Clustering, Customer Lifetime Value, Propensity, Predictive Analytics, Algorithm, Time-Series

Send similar jobs by email
77797/JK
Boston, Massachusetts
US$175000 - US$190000 per year
  1. Permanent
  2. Statistical Analyst

Similar Jobs

Salary

US$155000 - US$175000 per year

Location

Hartford, Connecticut

Description

Are you ready for the next challenge within your advanced analytics career?

Salary

US$160000 - US$200000 per year

Location

Richmond, Virginia

Description

Do you have a background in pricing or customer analytics, and have taken a company through a digital transformation?

Salary

US$115000 - US$130000 per annum

Location

New York

Description

This position requires you to build models in python or R and to look at in bound and out bound data!

Salary

US$125000 - US$155000 per year

Location

New York

Description

Are you a team manager who is still hands on and very passionate about sports?

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.

Drawing the Line Between Work and Family When Working Remotely

So, you’ve been told to work from home. Finally, more time with the family… Wait, more time with the family? How will you get your work done while also homeschooling your children? Maybe you’re married and your spouse is home, too. The routine of work has been disrupted, and though many businesses were already turning to remote work, this is something else.  So, how do you morph from leaving the house to go to the office to simply walking into your kitchen or home office to begin your day? In other words, how do you draw the line between work and family when you’re working from home? We know it can be difficult and unsettling in this troubled time, so we have a few tips to get you started. Getting Started in Your Remote Working Lifestyle DEFINE YOUR WORK SPACE What room can you designate in your house to be your “office.” It’s best to have someplace with a door, but this isn’t always possible. Is it the kitchen table? Ok, but this will mean you need to set strict ground rules about the hours you’re “on.” Make sure everyone understands when you’re “at work.” Whether it’s your kitchen table, a quiet room, or the end of your sofa with your laptop, these are your remote working tools. In some cases, it may even be a good idea to invest in noise-canceling headphones to help you stay focused. HAVE SET HOURS Define what hours you’re working and stick to them. Begin and end your day at the same time. Don’t forget to schedule breaks – coffee break, lunch, a stretch of the legs – around the same time each day as well. Work with your team to set hours for when you’ll be online working and respond to off-hour messages within your working hours. Without designated hours, it can feel like you’re constantly available and always “on” blurring the lines between work and family. Get some fresh air when you can. Step outside for a walk or a coffee, whatever brings you outside can help recharge and energize you for the work ahead. ENSURE YOU HAVE THE RIGHT TOOLS Remote working apps, videoconferencing tools, and cloud-based filing systems help ensure the job gets done. Make sure you keep your passwords in a safe place and be extra cautious when logging in from a new location. Is your computer up-to-date? Does it have all the security measures and capacity in place for the additional online tools and apps you may need to add? Making sure you address these things can help to solidify your workspace and ensure you’re able to meet with your team online and get the job done. FOLLOW THE 20-20-20 RULE The American Academy of Ophthalmology recommends the 20-20-20 rule: every 20 minutes look away from your screen and focus your eyes on something 20 feet away for 20 seconds. TAKE A BREAK FROM TALKING ABOUT WORK If you’re not used to working-from-home, loneliness can quickly set in. Remember those quick hallway chats or discussions over lunch or coffee? Take that impulse and use it when talking with your team. Have a virtual coffee break. Take a break from work and talk about hobbies, something funny that happened to you, or even just how you’re feeling away from everyone. You won’t be alone in these feelings with everyone in the same work-from-home boat. These tips can help you put your best foot forward for your remote working lifestyle. But don’t forget, you can use these same rules for family time, too. In the wake of work-from-home policies, remote working, and the shifting landscape of working outside the office, technology careers are prime opportunities to both gain increased knowledge in your chosen field or begin your career path.  If you’re interested in remote Big Data & Analytics opportunities, we may have a role for you. Take a look at our current vacancies or contact one of our expert consultants to find out more.   For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.   For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.  

How Computer Vision Engineers Develop the Eyes of AI

Facial Recognition software. Autonomous vehicles. Drone delivery. Robotics in manufacturing. 3D Printing. No longer the stuff of science fiction, these advancements are at the heart of the next evolution in the digital age. Developments are not just being made in the tech hubs of Silicon Valley, Austin, or New York, but in the mid-West. Ann Arbor, Michigan home to the University of Michigan and not too far from where Henry Ford first introduced mass production with the help of automation has been advancing robotic technologies across a variety of fields.  Giving machines their own set of eyes does require someone to ensure they have the right information to do their jobs. Enter the Computer Vision Engineer. It’s estimated this field will see a rise of 19% demand through 2026. It’s also a relatively small field with only 5,400 new job openings. So, like many professions, demand is high yet a shortage remains of those Data professionals with the right skillsets. The Business of a Computer Vision Engineer While there are a variety of roles within the field of Computer Vision, the role of Computer Vision engineer focuses on two areas. Those areas are: Writing code in Python/C++ Integrate Data Visualization, image analysis, and imaging simulation controls In addition to these areas, these scientists focus on research, implementation, reaching across teams both human and machine to help solve real world problems. And as important as knowledge and application theory are, it’s the hands-on experience which raises the bar for most employers and client companies.  Using image recognition, machine learning, and segmentation can help machines learn to differentiate various images. Being able to “see” what the computer may see and correcting it to ensure it’s more like human vision takes a special skillset. This can include: Computer Vision librariesDatabase managementComponent or object-oriented softwareAnalytical, logical, and critical thinkingClear reasoning It’s these skillsets along with a background in mathematics and computer languages like C++ which pave the Computer Vision engineer career path.  The Future of Computer Vision  The days of the generalist are long behind us. Now, more than ever, technologies like machine vision require a dedicated focus. With every field from healthcare to law enforcement to manufacturing utilizing these technologies, the future of Computer Vision performs a broader range of functions.   In Ann Arbor, at the University of Michigan and in partnership with Ford Motor Company, advancements race through every field not the least of which is manufacturing. As they transition toward full automation using the Internet of Things and more autonomous processes, it’s even more important to ensure Computer Vision models understand what they’re “seeing.” Computer Vision engineers will help to advance technologies which make machines easier to train and more easily figure out images better than they do now. Used in conjunction with other technologies like neural networks and other subsets of AI, machines will be able to see and interpret in the same way humans see and interpret.  And as far as we’ve come, there remains more applications and benefits not yet explored. The possibilities are endless. Current and future advancements will pave the way for AI to be as human as we are bringing our once science fiction ideas to life.  One Final Thought… Though Computer Vision engineering can be drilled down to even more focused professions, the term itself is broad. But the specializations are basic with a demand for not only highly skilled professionals with the right educational background, but also hands-on experience. This detail is more important now than ever before, especially for Computer Vision teams seeking leadership roles who can take their applications to the next level and on a global scale.  Some of the basic specializaitons include, but are not limited to: Camera imaging geometryFeature detection and matchingImage classification and scene analysis In the wake of work-from-home policies, remote working, and the shifting landscape of working outside the office, technology careers are prime opportunities to both gain increased knowledge in your chosen field or begin your career path.  If you’re ready to take the next step in your career, we may be able to help. Take a look at our current vacancies or get in touch with one of our expert consultants to learn more.   For our West Coast Team, contact us at (415) 614 - 4999 or send an email to sanfraninfo@harnham.com.   For our Mid-West and East Coast teams contact us at (212) 796-6070 or send an email to newyorkinfo@harnham.com.  

Recently Viewed jobs