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Senior Machine Learning Scientist
Salary

US$180000 - US$220000 per annum

Location

San Francisco, California

Description

This opportunity is for someone looking to join a data-driven media startup. The role provides enormous opportunities to grow and take on new responsibilities.

Reference:

109564-JS

Expires on
Jenna Schmitz
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Software Engineer (Computer Vision)
Salary

US$170000 - US$200000 per annum

Location

San Francisco, California

Description

As a Senior Software Engineer for this company, you will build out a team in the autonomous driving space. Apply if you have experience with C++ Python & LiDAR

Reference:

108555/JS

Expires on
Jenna Schmitz
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Director, Analytics
Salary

US$150000 - US$160000 per annum

Location

Boston, Massachusetts

Description

Do you have progressive experience managing agile analytics teams at Marketing & Advertising companies?

Reference:

00068/GL

Expires on
George Little
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SVP, Measurement
Salary

US$250000 - US$260000 per annum

Location

New York

Description

An innovator within TV Ad Measurement is in the market for an SVP-level leader to preside over both the Custom Analytics and Data Science teams!

Reference:

108471/GG4

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Greffen George
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Director of Customer Analytics
Salary

US$150000 - US$170000 per annum

Location

New York

Description

We have a client whose mission is centered around helping those in need. Apply today to be a part of their impact!

Reference:

110322VB3

Expires on
Vallon Barnes
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Senior Autonomy Engineer
Salary

US$130000 - US$145000 per annum

Location

Washington, District of Columbia

Description

Click to read more about a role that would allow you to work on developing autonomous systems for defense purposes!

Reference:

85792/AN0419

Expires on
Annie Nasharr
Annie Nasharr
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SLAM Engineer
Salary

US$115000 - US$135000 per annum

Location

Detroit, Michigan

Description

Join this growing navigation team at a Michigan based start-up

Reference:

081120/AN0419

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Annie Nasharr
Annie Nasharr
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Autonomous Systems Engineer
Salary

US$120000 - US$150000 per annum

Location

District of Columbia

Description

This company is working on solving the biggest issues within autonomy and robotics for the US government.

Reference:

32670-MR4

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Mitchell Resor
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Embedded Systems Engineer
Salary

US$70000 - US$100000 per annum

Location

Ann Arbor, Michigan

Description

An autonomous robotics company in Michigan is looking to add an Embedded Systems Engineer to their fast-growing team.

Reference:

109731-MR2

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Mitchell Resor
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Robotics PCB Engineer
Salary

US$65000 - US$95000 per annum

Location

Ann Arbor, Michigan

Description

Have you designed, printed, and tested PCBs for robotic/autonomous systems?

Reference:

109741/AN0419

Expires on
Annie Nasharr
Annie Nasharr
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Lead Computer Vision Engineer - Medical Imaging
Salary

US$170000 - US$190000 per annum

Location

New York

Description

This company is using computer vision to make advancements in Telehealth.

Reference:

060120/AN00419

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Annie Nasharr
Annie Nasharr
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Principal Robotics Engineer
Salary

US$170000 - US$180000 per annum

Location

Pittsburgh, Pennsylvania

Description

Are you an expert in robotic navigation and perception?

Reference:

109719/AN0419

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Annie Nasharr
Annie Nasharr
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624 result(s) found
Results per page 12 24 60

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.

Bridging the Gap: The Role of a DevOps Engineer

Siloed teams are swiftly becoming a thing of the past as organizations learn collaboration is key. Businesses are embracing transformation. But some may not know where to turn to help them manage such a massive restructuring of operations. Enter the DevOps Engineer. Yes, Virginia. The unicorn employee does exist. What is a DevOps Engineer? For many businesses, it’s a dream to find a technical person who can also communicate across departments. In the DevOps Engineer role is an IT Generalist who not only has a deep understanding of codes, infrastructure management, and agile familiarity but who also possesses interpersonal skills. It’s this combination that makes this role so imperative to businesses. Working across siloes and bringing teams together for collaboration bridges the gap between the technical and non-technical departments. One of their most important roles is as advocate. Moving from siloed teams to the more collaborative environment of a DevOps culture can be difficult for engineering team members. But as advocate for the benefits, the DevOps Engineer can explain it best to those with whom they’ve worked. Their technical expertise puts them on par with their peers and their interpersonal skills offer a way to communicate across the organization.   Want to Restructure Your Skills toward DevOps? If you’re an IT Generalist with great communication skills. DevOps Engineer could be your next role. But what skills do you need and how might you streamline what you already know into this key role for many businesses? Technical skills depend on team structure, technologies in place, and tools already in use. But the key element of a DevOps Engineer is their strong communication and collaborative skills. Can you morph your technical world into layman’s terms for the executives? Can you translate different needs across teams from QA testers to software developers, generalists and specialists alike? It’s this deep understanding which makes you so valuable to employers. For many organizations, this is the best of both worlds.  Knowing the pros and cons of available tools. Understanding the components of a delivery pipeline. And strong communication skills to bridge once siloed teams into a cohesive and collaborative environment. More technical skills include, but aren’t limited to System administration – such as managing servers, database deployment, and system patching just to name a few.Experience with DevOps tools – understand the lifecycle from building and infrastructure to operating and monitoring a product or service.Configuration management – experience with configuration management tools such as Chef, Puppet, or Ansible to automate admin tasks.Continuous Integration (CI) and Continuous Deployment (CD) – this is a core practice of DevOps. It’s this role’s approach to software development with tools to automate the building, testing, and deploying of software processes. System architecture and provisioning – ability to design and manage computer ecosystems whether in-office or in the cloud. Within this skillset is the importance of Infrastructure as Code (IaC). This is an IT management process that applies best practices from software development to cloud infrastructure management.  Collaborative management skills – while the CI/CD skills are core to the technical side, this is one of the key components for the soft skills required for a DevOps structure. In a Nutshell DevOps (Development + Operations) is a practice that involves new management principles and requires a cultural change. And a DevOps Engineer is the heart of the transformation. Yet they can’t do it alone. A good DevOps Team has more than just one engineer. It involves a mix of generalists and specialists to implement and improve these practices within the software development cycle. A few of these roles include:  DevOps evangelist Automation expert Software developer Quality assurance  If you’re interested in Big Data and Analytics, Harnham may have a role for you. Check out our current vacancies or contact 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.  

Kavya Kannan

Kavya Kannan

15. April 2021

News

Amped Up Analytics: Google Analytics 4

Google Analytics 4 has amped up data insights into the behaviors and preferences of your customers. Where once each touchpoint only tracked what had been clicked, GA4 is bringing it all together in a more wholistic approach to the customer journey. As the fourth quarter of 2020 dawned, Google upped its game. Crafting a compelling array of features with machine learning at its core, this new platform offers a more customer-centric approach to data-driven insights, rather than split data across platforms and devices.   Though still in its infancy, there are some dramatic new changes afoot. And while it’s not a good idea to get rid of the old Universal Analytics platform before ringing in the new one, it is a good idea to understand what’s available now and what may come to be over time. Four Advantages to Google Analytics 4.0 From our desktop to our laptop to our smartphone, we carry our office in our pocket or on our lap. So, what better way to integrate what was once called “App + Web properties” into a more cohesive trackable measurement of data. Add to this the privacy protocols in place to protect customers, and Google Analytics 4 offers flexibility for future cookieless tracking and permissions, and advantages are revealed. Combined Data and Reporting Rather than focusing on one property (web or app) at a time, this platform allows marketers to track a customer’s journey more holistically.  The platform’s premise is that there is a pattern everyone follows. From the moment a customer visits your website to clicks on a button subscribing to your newsletter or blog – Acquisition and Engagement. To the moment your customer makes a purchase, is happy with the product or sevice, and comes back again – Monetization and Retention.  Designed for marketers who want to track users across multiple formats, Google Analytics 4 hopes to solve with Data Streams. These Data Streams merge to paint a picture of the customer journey from website visit to purchase. A Focus on Anonymized Data This anonymization answers the call to Data Privacy and third-party data collection. Crafting a unified user journey centered around machine learning to fill in any gaps, marketers and businesses have a way to get the information they need without diving into personal data issues. This is a key change in that Google is moving away from client-side focus and using server-side and customer-centric capabilities. With GDPR and privacy laws in full swing, marketers face enhanced privacy regulations as cookies are phased out or blocked. Predictive Metrics and Audiences Using Machine Learning to predict future transactions is a game changer for the platform. These predictive metrics for e-commerce sites on Google properties allow for targeted ads to visitors who seem most likely to make a purchase within one week of visiting the site.  Though focused on e-commerce sites now and based on transactions and revenue, there is an opportunity for marketers to identify and convert based on such leads as video views or form submissions. Machine Learning-Driven Insights The launch announcement for GA4 explains it “has machine learning at its core to automatically surface helpful insights and gives you a complete understanding of your customers across devices and platforms.” Machine Learning-driven insights include details that elude human analysts.  What These Changes Mean on the Digital Frontier We’re all reaching for higher value and Google Analytics 4.0 brings it into one unified platform for the future. As we make the shift from traditional Google Analytics to its 4.0 version, there is opportunity to get more creative.   Wondering if you should upgrade? This article breaks down the pros and cons to help you decide.  If you’re interested in Big Data & Analytics, Harnham may have a role for you. Check out our current vacancies or contact 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.  

Joshua Poore

Joshua Poore

08. April 2021

News

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