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Distinct experience in advanced probability, statistics, machine learning, big data processing, analytics, and pipelining using Spark is essential, as well as experience in deep learning, generative AI, LLMs, and NLP. This role involves developing data science solutions, mentoring and imparting knowledge about machine learning and data concepts and techniques, as well as driving adoption of standards, processes, and tools to achieve high operational efficiency.
$242,000 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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The Data Science Team within Asset Management Technology, Quant Research and Development, is seeking a highly motivated and technically proficient data scientist who is passionate about applying advanced technologies in investment management domain.
$218,000 a yearFull-timeExpandApply NowActive JobUpdated 2 days ago - UpvoteDownvoteShare Job
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The Principal Scientist, Bioinformatics Data Science, is a critical contributor to data analytics and engineering focused on accelerating our R&D programs and expanding our FORCE therapeutic delivery platform.
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Minimum of 6 years of experience in pharmaceutical research, with an emphasis on data engineering, data science, data integrity, and data governance. You will work closely with data scientists, data engineers, and platform engineers to scale the Vertex Data Platform, which is Vertex's cutting edge technology ecosystem for Data Engineering, Data Science, and Advanced Analytics.
$210,120 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Experience leveraging complex data to drive business decisions, hands-on experience in data science methodologies (predictive analytics, machine learning, patient level data triggers) using R, Python, Databricks and deep knowledge of Qlik, PowerBI, Tableau for visualization.
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Technical understanding of machine learning algorithms; experience with deriving insights by performing data science techniques including classification models, clustering analysis, time-series modeling, NLP; technical knowledge of optimization is a plus.
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The scientist will work on a team with deep expertise in computational biology, data science, genomics, and pharma/biotech partnerships – with the unified goal of deriving maximal value from Caris’ data for external and internal research efforts to advance cancer care.
Full-timeExpandApply NowActive JobUpdated 17 days ago - UpvoteDownvoteShare Job
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5+ years of experience in data analysis or data science, with 3+ years focusing on machine learning problems, ideally in a relevant space (KYC, sanctions detection, anti-fraud detection, treasury management, crypto/blockchain data science.
$195,000 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Current PhD - Data Science Internship - Summer 2025. If you're interested in a long-term career at Capital One, the Data Science internship could be a great way to begin your career journey.
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Master’s degree in Bioinformatics, Computational Biology, Biostatistics, Data Science, or related field with 3-5 years’ experience working directly with metabolomics and other -omics data.
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Experience in Data Science/cloud-based machine learning platforms (AWS Bedrock, AWS Sagemaker, Snowflake Cortex etc. Data Security: Experience in working within compliance (e.g.: quality, regulatory – data privacy, GxP, SOX) and cybersecurity requirements is a plus.
$111 an hourExpandApply NowActive JobUpdated 23 days ago - UpvoteDownvoteShare Job
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PhD. in Molecular Biology, Biochemistry, Virology, Immunology or a related field, with a strong background in protein science or biotechnology. Stay abreast of the latest scientific advances in life science, proteomics and drug delivery and apply cutting-edge techniques and methodologies in your research.
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Experience or academic work with large scale data analysis Data Science Internship. New York City (Hybrid On-Site): $149,000 - $149,000 for Data Science Intern San Francisco, California (Hybrid On-site): $158,000 - $158,000 for Data Science Intern Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate’s offer letter.
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Identify and develop the data operational processes to optimize, monitor and improve data quality and outcome for the data engineering, analytics and data science users and producers of data.
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Advanced degree in Computer Science, Engineering, Mathematics, Computational Statistics, Operations Research, Quantitative finance or related technical fields. 5+ years of prior work experience as a data scientist if MS degree, 3+ years with Ph. D. degree.
$218,000 a yearFull-timeExpandApply NowActive JobUpdated 17 days ago
data science plus jobs Title: science in Boston, MA
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The Best Remote Jobs: Where & How to Find Them
The Covid-19 pandemic hasn’t been easy on any of us, but if there’s one silver lining, it’s the fact that remote work has grown in popularity because of it. Companies that previously weren’t open to their employees working remotely were suddenly forced into allowing it. Since then, they've realized that much of their workforce is happier and more productive. Naturally, this has led to more remote job openings, which is great if you’re interested in this type of position. Read on to learn more about the best remote jobs and where to find them.
How to Write a Short Bio
First impressions can be tricky. When meeting someone in person, it’s likely you have an elevator speech. These short, practiced introductions can help you share more about who you are, what you do for work and other facts about you. While this works well in a live, in-person context, there are many cases where professionals “meet” someone via written form - like social media, a resume, or published work. In these cases, your bio works as your first impression. So, here’s a step-by-step guide on how to write a short bio.
How to Conduct a Performance Review (With Examples)
In a world where the smallest mistake can cost your business tens of thousands in lost revenue, your talent is key to keeping your edge on the market and driving growth. However, managing a workforce of any size can be a challenge. Employees come with their own particular skill set, ambitions and flaws. So, it can be difficult to uncover their individual drivers. Not to mention the challenges brought on by the hybrid and remote working models where in-person interactions have become few and far between.
How to Recruit Passive Candidates
Learning to recruit passive candidates is a different ballgame than recruiting active ones. While an active candidate is someone who is currently looking for a new job, a passive candidate tends to be the opposite. Passive candidates are either already working or not looking to work. So, instead of these candidates coming to you, you'll have to find them and reach out to them first.
How to Effectively Recruit Employees
Today, hiring and retaining talent looks much different than it did only two or three years ago. Financial instability and the strain on our mental health brought on by the pandemic has made everyone more wary and selective of their workplace and employer. Whereas in the past people might have prioritized promotions and financial reward, today they look at other factors such as workplace flexibility, personal fulfillment and values alignment.
How Many Hours is Part-Time vs. Full-Time Work?
Growing up you watched your parents shuffle to and from the office, held hostage to their 9 to 5. If jammed-packed schedules and deadlines sound frightening, you might consider pivoting your search to part-time jobs. In fact, even employers have shifted their preference, selecting more people open to the idea of flexible working hours.
How to Make a Job Offer More Competitive
Money alone makes it hard to attract and retain top-notch candidates, especially when you are competing with larger businesses and corporations in your industry. So, instead of focusing on money, figure out how to make a job offer more competitive when you can't offer more money.