1

Evening Data Scientist Machine Learning Jobs (NOW HIRING)

As a Data Scientist Machine Learning, you will work within a small data science team focusing on predictive modeling, natural language processing, computer vision, recommender systems, and OCR ...

ATG is an Equal Opportunity/Affirmative Action Employer Minorities/Females/Vets/Disability Job Summary We are seeking a Data Scientist / Machine Learning Engineer to support advanced analytics and ...

next page

Showing results 1-20

Evening Data Scientist Machine Learning information

See salary details

$37.5K

$122.7K

$196.5K

How much do evening data scientist machine learning jobs pay per year?

As of Jul 7, 2026, the average yearly pay for evening data scientist machine learning in the United States is $122,738.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,500.00 and $136,000.00 per year, depending on experience, location, and employer.

What is the difference between Evening Data Scientist Machine Learning vs Evening Data Analyst?

AspectEvening Data Scientist Machine LearningEvening Data Analyst
Required CredentialsBachelor's or Master's in Data Science, Computer Science, or related fields; knowledge of machine learning frameworksBachelor's degree in Data Analysis, Statistics, or related fields; proficiency in data visualization tools
Work EnvironmentResearch-focused, developing models, programming in Python/R, working with large datasetsData reporting, cleaning, visualization, and basic statistical analysis
Employer & Industry UsageTech companies, finance, healthcare, research institutionsBusiness, marketing, retail, finance sectors

While both roles involve working with data in the evening, Evening Data Scientist Machine Learning focuses on developing predictive models and advanced algorithms, requiring programming and machine learning expertise. In contrast, Evening Data Analyst emphasizes data interpretation, reporting, and visualization, often with less emphasis on complex modeling. The roles differ mainly in technical depth and scope but share a common goal of deriving insights from data during evening hours.

What cities are hiring for Evening Data Scientist Machine Learning jobs? Cities with the most Evening Data Scientist Machine Learning job openings:
What are the most commonly searched types of Data Scientist Machine Learning jobs? The most popular types of Data Scientist Machine Learning jobs are:
What states have the most Evening Data Scientist Machine Learning jobs? States with the most job openings for Evening Data Scientist Machine Learning jobs include:
Data Scientist - Machine Learning

Data Scientist - Machine Learning

Caris Life Sciences

Boston, MA โ€ข On-site

$125K - $150K/yr

Full-time

Posted 17 days ago


Job description

At Caris, we understand that cancer is an ugly word-a word no one wants to hear, but one that connects us all. That's why we're not just transforming cancer care-we're changing lives.

We introduced precision medicine to the world and built an industry around the idea that every patient deserves answers as unique as their DNA. Backed by cutting-edge molecular science and AI, we ask ourselves every day:"What would I do if this patient were my mom?"That question drives everything we do.

But our mission doesn't stop with cancer. We're pushing the frontiers of medicine and leading a revolution in healthcare-driven by innovation, compassion, and purpose.

Join us in our mission to improve the human condition across multiple diseases. If you're passionate about meaningful work and want to be part of something bigger than yourself, Caris is where your impact begins.

Position Summary
Caris Life Sciences is seeking a Data Scientist working in Machine Learning to leverage one of the world's largest multimodal cancer datasets to develop novel machine learning models that integrate molecular and clinical data to advance understanding of cancer biology and improve patient outcomes. This role sits at the intersection of modern machine learning and oncology.
Working closely with machine learning scientists, computational biologists, and oncology domain experts, the successful candidate will build models spanning deep learning and statistical approaches, deploy predictive capabilities into the Caris clinical diagnostic platform, publish scientific results, and support collaborations with biopharma partners. This is a handson research role in a highly collaborative environment with significant opportunity to shape scientific direction.
Job Responsibilities

  • Design, build, and iteratively refine novel machine learning models using modern architectures and classical statistical methods to address translational oncology questions.
  • Develop and apply multimodal modeling approaches integrating RNAseq expression data with mutations, copy number alterations, fusions, protein markers, and clinical metadata.
  • Translate model outputs into improvements on the Caris clinical diagnostic platform to support improved treatment predictions.
  • Publish results in peerreviewed journals and present findings at scientific conferences and internal forums.
  • Support collaborations with biopharma partners by providing analytical expertise, developing custom analyses, and communicating results to external stakeholders.
  • Stay current with advances in machine learning research, tools, architectures, and emerging development paradigms.


Required Qualifications

  • Ph.D. in Computer Science, Computational Biology, Applied Mathematics, or a related quantitative field; or M.S. degree with 3+ years of relevant professional experience.
  • Deep familiarity with modern machine learning approaches including representation learning, attentionbased architectures, foundation models, and selfsupervised learning.
  • Working knowledge of statistical modeling concepts relevant to clinical data, including generalized linear models, survival analysis, and Bayesian methods.
  • Demonstrated experience building and applying novel machine learning models beyond offtheshelf solutions.
  • Proficiency in Python and the scientific computing ecosystem (PyTorch or TensorFlow, scikitlearn, pandas, NumPy, SciPy).
  • Strong written and verbal communication skills.
  • Familiarity with Linux environments and Git.
  • Proficient in Microsoft Office Suite including Word, Excel, Outlook, and business internet tools.


Preferred Qualifications

  • Understanding of cancer and molecular biology with experience using largescale genomics datasets.
  • Peerreviewed publications in machine learning or computational biology.
  • Experience with computer vision for digital pathology
  • Experience with natural language processing of EHR or realworld data.
  • Experience deploying models in cloud environments and MLOps practices.


Physical Demands

  • Primarily officebased role requiring extended periods of sitting and computer use.


Training

  • All jobspecific, safety, and compliance training is assigned based on job functions.


Other

  • May require periodic travel and occasional evening or weekend work.

Annual Hiring Range

$125,000 - $150,000

Actual compensation offer to candidate may vary from posted hiring range based upon geographic location, work experience, education, and/or skill level. The pay ratio between base pay and target incentive (if applicable) will be finalized at offer.

Conditions of Employment: Individual must successfully complete pre-employment process, which includes criminal background check, drug screening, credit check( applicable for certain positions) and reference verification.

This job description reflects management's assignment of essential functions. Nothing in this job description restricts management's right to assign or reassign duties and responsibilities to this job at any time.

Caris Life Sciences is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, gender, gender identity, sexual orientation, age, status as a protected veteran, among other things, or status as a qualified individual with disability.