Harnham
SEARCH
Shortlist

SENIOR COMPUTATIONAL BIOLOGIST

San Francisco, California
US$160000 - US$185000 per annum + BENEFITS
Apply Save job

SENIOR COMPUTATIONAL BIOLOGIST

SAN FRANCISCO, CA

$160,000 - $185,000 + BENEFITS

THE COMPANY

This pharmaceutical startup is advancing drug discovery through artificial intelligence, machine learning, and deep learning. As a member of the data science organization, you will utilize your experience in analyzing multiomic data including NGS, RNAseq and GWAS data to drive scientific discovery and advancement.

THE ROLE

Responsibilities will include:

  • Applying computational biology and bioinformatics techniques to RNA seq and GWAS data
  • Collaborating with wet lab scientists to drive scientific discovery
  • Developing computational pipelines that integrate new biological data
  • Hands on coding and algorithm development

YOUR SKILLS AND EXPERIENCE

Your skills include:

  • PhD in computational biology, bioinformatics, or related fields
  • Demonstrated hands on experience applying Python to multiomic data including NGS, RNAseq and GWAS
  • Start-up experience is a plus

THE BENEFITS

  • Base salary range of $160,000 - $185,000
  • Comprehensive healthcare, vision, and dental
  • Huge internal growth opportunities, comprehensive stock package, and more!

HOW TO APPLY

Please email your CV to Alyssa Liew at the address .

Apply Save job
Send similar jobs by email
AL/87986
San Francisco, California
US$160000 - US$185000 per annum + BENEFITS
  1. Permanent
  2. Bioinformatics

Similar Jobs

Director of Bioinformatics - Imaging
Salary

US$170000 - US$200000 per annum + EQUITY, BENEFITS

Location

Palo Alto, California

Description

Seeking a new challenge revolving around the development of statistical and machine learning methods for image analysis?

ADD TO SHORTLIST
Senior Computational Biologist
Salary

US$150000 - US$170000 per annum + EQUITY, BENEFITS

Location

Mountain View, California

Description

Have a passion for understanding the latest in antibody discovery?

ADD TO SHORTLIST
DIRECTOR OF DATA
Salary

US$190000 - US$210000 per annum + BENEFITS

Location

San Francisco, California

Description

Lead a data team to grow a more sustainable food solution!

ADD TO SHORTLIST
Senior Computational Chemist
Salary

US$140000 - US$170000 per annum

Location

San Francisco, California

Description

Use your skills in small-molecule drug discovery!

ADD TO SHORTLIST

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.

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

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.  

Elizabeth Sobel

Elizabeth Sobel

25. March 2021

News

Recently Viewed jobs