Data Science Remote Jobs

Remote Jobs in USA

We help the best talent in the Data Science market find rewarding careers.

Deep Learning models is one of the most sought-after skillsets for employers. Data science requires those who work in the field to often write sophisticated algorithms that extract insights from large and complex data sources.

Our specialty is matching highly experienced and skilled talent, with world leading organisations and disruptive start-ups who value the hidden insights data scientists can extract from their data.

View our latest Data Science Remote Jobs.

Latest Jobs

Salary

US$150000 - US$175000 per annum

Location

Manhattan, New York

Description

A health-tech company is looking for an NLP expert to aid them in their mission to revolutionize healthcare utilizing artificial intelligence.

Salary

US$110000 - US$130000 per annum + Equity

Location

New York

Description

This role at an exciting startup is perfect for anyone looking for an opportunity with lots of growth potential, and the ability to make it your own!

Salary

US$170000 - US$200000 per annum

Location

San Francisco, California

Description

Data Science leader with experience building out data science teams, and leading teams developing models into production.

Salary

US$170000 - US$200000 per annum

Location

New York

Description

Data Science leader with experience building out data science teams, and leading teams developing models into production.

Salary

US$110000 - US$130000 per annum + plus equity

Location

San Francisco, California

Description

This role at an exciting startup is perfect for anyone looking for an opportunity with lots of growth potential, and the ability to make it your own!

Salary

US$182887 - US$207272 per annum

Location

Salt Lake City, Utah

Description

Senior Data Scientist with a passion for optimizing work flows and building ML tools for Data Science; experience with Kubernetes, AWS sagemaker, AzureML

Salary

US$150000 - US$190000 per annum

Location

San Francisco, California

Description

This is the world's largest brand-name apparel company. Designing casual wear and related accessories for men, women, and children.

Salary

US$160000 - US$200000 per annum + Competitive Benefits

Location

San Diego, California

Description

A growing fintech start up addressing some of the world's largest problems in the credit space.

Salary

US$110000 - US$130000 per annum

Location

San Francisco, California

Description

This role at an exciting startup is perfect for anyone looking for an opportunity with lots of growth potential, and the ability to make it your own!

Salary

US$182887 - US$213369 per annum

Location

Salt Lake City, Utah

Description

Data Scientist with a passion for Biotech and healthcare using DS to help with drug discovery, small molecule and embedded chemical structures experience

Salary

US$130000 - US$150000 per annum

Location

New York

Description

A technology-based remote video game start-up with significant funding is looking for its first data scientist skilled in machine learning.

Salary

US$110000 - US$130000 per annum + plus equity

Location

New York

Description

This role at an exciting startup is perfect for anyone looking for an opportunity with lots of growth potential, and the ability to make it your own!

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.

How Big Data and Risk Analytics Can Help Fight Climate Change

Data is all around us. We use it to calculate our calories and our steps to ensure a healthy body. We use it track our packages and ensure delivery to the right location. We look to it to check the weather for exercise, driving conditions, and in extreme cases, safety preparedness. But, could we use it to fight climate change? Could we use it to reign in swiftly rising temperature changes which could affect our food and ecosystems?  Greener Choices for Greener Products People have more choice than ever before. They also have information at their fingertips and can see at a glance the benefits or the drawbacks of purchases. From how their food is grown to how far their food is delivered to the practices of companies from oil and gas producers to the wearables on their wrist. Climate change and Big Data have been linked, but mostly to determine greenhouse gases and effects of pollutants. But with the rise of consumer advocacy groups, farm-to-table traditions, micro-and macro-farming, and a desire to know more about what we’re putting into our bodies, consumers are dictating greener options from the markets. The Business of Climate Risk Analytics As consumers take note of climate change, companies are merging knowledge of climate change risk into their financial decision making. How will climate change their business practices? How will it be scaled based on how climate science rules inform financial risk assessments not yet developed? The markets need just as much information as consumers when it comes to climate risk. These assessments are intended to businesses determine consequences, responses, and likelihood of the impacts of their actions. Enter climate risk analytics. Climate Risk Analytics uses risk assessment and risk management based on natural disasters and their impact. However, the climate is not in a static state. It’s ever-changing and those changes are often in the extremes with little information related to averages. This complicates risk assessments as do the differences in regional projections. How AI Can Help Big data combined with climate risk analytics is getting an additional boost from artificial intelligence. AI techniques are being used for a variety of situations such as disease tracking, crop optimization, and monitoring everything from our heartbeat to endangered species. Solutions from advances in Deep Learning and Machine Learning could solve global environmental crises while assuaging financial risk with predictive modelling. Yet barriers to effective solutions from AI include cost and regulatory approval. But if these items weren’t an issue? We could determine such vital information as water availability and ecosystem wellbeing. Water and ecosystems aside, AI can help: Track and monitor endangered speciesImprove energy efficienciesOptimize wildlife conservation Fight poaching of endangered speciesTrack mosquito populations to prevent diseaseWarn populations of upcoming storms• Inform agriculture, health, and climate studiesDetermine water, forest, and urbanization changesSome vineyards in California use AI to determine if vines receive enough or too much water. AI’s ability to process large amounts of information quickly are a boon to the ever-changing climate, its risk assessments for businesses, and its benefits to consumers and investors who want to know what businesses are doing to keep everyone safe. In Honor of Earth Day This week we celebrate Earth Day. It’s a day to remember and honor the earth who gives us our air, our food, our animals, plants, fish, and so much more. From Greta Thunberg’s School Strike for Climate to Naomi Klein’s book, The (Burning) Case for a Green New Deal, climate is front and center of our thoughts and our survival. Want to be part of the movement working with Climate Risk Analytics or the effect of Artificial Intelligence in our environment? Harnham may have a role for you. From Big Data & Analytics to the Life Sciences, there’s something for everyone interested in the Data industry. 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.  

Making Sense of Unstructured Data with NLP

Natural Language Processing. It seems a simple enough explanation. The idea is to make computers sound like native speaking humans regardless of their language. Except there’s one problem. When we speak, we don’t follow our own rules of grammar. We use idioms, metaphors, abbreviations, and oftentimes use more body language to communicate than we realize.  So, what’s a poor machine to do when confronted with such an unstructured melee of data? Well, since semantics is not what you say it’s how you say it, we must teach computers to read between the lines. Of code. Enter NLP. The semantics of human language written for a machine to help make sense of our human behaviors gets organized. The Perfect Imperfections of Language Computers require structure. Natural language does not. Teaching machines how we communicate is no easy task, and yet we use machines that can do this every day. By combining technology and Machine Learning we begin to teach computers how to understand us. We teach them how to interpret and determine what it was we want done. When you’re asking Siri or Alexa a question, you’re helping them to learn how you ask, so they can better respond, and they make you more efficient. It’s a win-win for everyone. In business, using NLP techniques to drive business decisions is even more important. Now, the computer must decide what information is the most valuable to pull from a pile of Data. Understanding our choices, our tone, even the words we choose to use, helps our machines learn what we want to do or need done. Where is NLP Used? Since we use different rules when we speak than when we write, our computers learn how we talk and how to use language more naturally. Wondering where NLP might be used? In a word or two? Nearly everywhere. You are scheduling a meeting and when it’s time, a calendar reminder pops into your phone which says estimated drive time to the meeting based on traffic conditions in your area. Or you ask Alexa to play your favorite music list from Pandora.  Every touchpoint in this scenario is using NLP. We naturally might get into our car, ask our Virtual Assistant navigation system for directions, or to play our favorite music. Our choices don’t fit in a box and may not be logical, but the more we teach the machines, the closer they may get to understanding the nuances of our language. Here are 5 more ways we use NLP every day: Predictive text on your phone or in your Word document. Chatbots and Virtual Assistants to ensure customers are acknowledged in a timely manner, answer basic questions or redirect to appropriate personnel, and making suggestions to improve the customer experience.Curating social media feeds to determine customer needs and interest.Grammar correction software so our emails and business documents are error-free.Analyzing customer interactions using comments and reviews for customer feedback about a product or service. There’s a ton of information to be filtered, sorted, sifted, and analyzed, and NLP is just one of the tools Data Scientists use. Interested in the subfield of NLP? Check out this article for 6 techniques you need to know to get started. Already well-versed in the industry and looking for a new challenge? If you’re interested in Big Data and Analytics, Advanced Analytics, Life Sciences, Data Science, or any of our Data professional fields, we may have a role for you. Review 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.  

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