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Temporary Predictive Modeling Jobs in California

AllSTEM Connections

Business Analyst

Universal City, CA · On-site

$156K/yr

... and predictive modeling. Equal Opportunity Employer / Disabled / Protected Veterans The Know Your Rights poster is available here: The pay transparency policy is available here: For temporary ...

Avathon

Engineering Manager

Pleasanton, CA · On-site

$180K - $210K/yr

Establish MLOps frameworks to support continuous model training, deployment, and monitoring ... Understanding of predictive maintenance or asset performance use cases * Experience with LLM ...

Prescient Edge

Senior Scientist

Riverside, CA · On-site

$95K - $130K/yr

... predictive analysis, and operational effectiveness. * Apply scientific and analytical methods to ... Develop models, simulations, and analytical frameworks to support mission decision-making.

Avathon

AI Engineer

Pleasanton, CA

$116K - $159K/yr

Implement and productionize transformer-based models and GenAI workflows for enterprise use cases ... temporary roles are not eligible for the above benefits. Compensation Pay Range: $110k - $130k ...

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Temporary Predictive Modeling information

What jobs will no longer exist in 2030?

Predictive modeling jobs are expected to evolve significantly by 2030 due to advancements in AI and automation. Roles that rely heavily on manual data processing or routine analysis may diminish as machine learning tools become more capable, but specialized predictive modeling positions that require complex analysis and domain expertise will continue to be in demand. Continuous learning in programming, statistics, and AI tools will be essential for future professionals in this field.

Is 40 too late for data science?

Age is not a barrier to entering a predictive modeling or data science role. Many professionals successfully transition into data science later in their careers by acquiring relevant skills such as programming, statistics, and machine learning, often through online courses or certifications. Employers value experience and problem-solving ability, making it possible to start a data science career at age 40 or older.

How do you do predictive modeling?

Predictive modeling involves analyzing historical data using statistical techniques and machine learning algorithms to develop models that forecast future outcomes. It requires data cleaning, feature selection, model training, and validation, often using tools like Python or R. Strong analytical skills and understanding of algorithms are essential for effective predictive modeling.

What is the difference between Temporary Predictive Modeling vs Data Analyst?

AspectTemporary Predictive ModelingData Analyst
Required CredentialsBachelor's in Statistics, Data Science, or related field; experience with modeling toolsBachelor's in Data Science, Statistics, or related; proficiency in data analysis tools
Work EnvironmentProject-based, focused on building predictive models for specific business needsOngoing data interpretation, reporting, and visualization tasks
Employer & Industry UsageUsed in industries like finance, marketing, and tech for predictive insightsCommon across industries for data reporting and analysis
Search & Comparison IntentSeeking temporary roles focused on predictive modeling tasksLooking for data analysis roles involving data interpretation

Temporary Predictive Modeling roles focus on developing specific predictive models for short-term projects, requiring specialized skills in modeling techniques. Data Analysts perform ongoing data interpretation and reporting, often with broader data handling responsibilities. While both roles require analytical skills, their focus and scope differ significantly.

Is predictive modeling difficult?

Predictive modeling as a job involves analyzing data, selecting appropriate algorithms, and validating models, which can be complex depending on the project's scope and data quality. It requires skills in statistics, programming, and data analysis tools like Python or R, and often involves continuous learning to stay updated with new techniques. The difficulty varies based on experience and the complexity of the problems being addressed.
What are the most commonly searched types of Predictive Modeling jobs in California? The most popular types of Predictive Modeling jobs in California are:
What are popular job titles related to Temporary Predictive Modeling jobs in California? For Temporary Predictive Modeling jobs in California, the most frequently searched job titles are:
What job categories do people searching Temporary Predictive Modeling jobs in California look for? The top searched job categories for Temporary Predictive Modeling jobs in California are:
What cities in California are hiring for Temporary Predictive Modeling jobs? Cities in California with the most Temporary Predictive Modeling job openings:
Temporary Predictive Modeling jobs near you
TEMP - Senior Scientist, Computational Chemistry (Remote, Hybrid, or San Diego)

TEMP - Senior Scientist, Computational Chemistry (Remote, Hybrid, or San Diego)

Neurocrine Biosciences, Inc.

San Diego, CA • On-site, Remote

$97K - $132K/yr

Full-time

Posted 18 days ago

Job description

Who We Are:
At Neurocrine Biosciences, we pride ourselves on having a strong, inclusive, and positive culture based on our shared purpose and values. We know what it takes to be great, and we are as passionate about our people as we are about our purpose - to relieve suffering for people with great needs.
What We Do:
Neurocrine Biosciences is a leading neuroscience-focused, biopharmaceutical company with a simple purpose: to relieve suffering for people with great needs. We are dedicated to discovering and developing life-changing treatments for patients with under-addressed neurological, neuroendocrine and neuropsychiatric disorders. The company's diverse portfolio includes FDA-approved treatments for tardive dyskinesia, chorea associated with Huntington's disease, classic congenital adrenal hyperplasia, endometriosis* and uterine fibroids,* as well as a robust pipeline including multiple compounds in mid- to late-phase clinical development across our core therapeutic areas. For three decades, we have applied our unique insight into neuroscience and the interconnections between brain and body systems to treat complex conditions. We relentlessly pursue medicines to ease the burden of debilitating diseases and disorders because you deserve brave science. For more information, visit neurocrine.com, and follow the company on LinkedIn, X and Facebook. (*in collaboration with AbbVie)
About the Role:
Neurocrine is expanding our R&D chemistry capabilities. In this exciting new role, you will be instrumental in the success of our growing computational chemistry team. The successful candidate will be responsible for the execution of computational driven methodologies to help design optimized compounds with balanced properties (targets, DMPK, in-vivo) in drug discovery programs, that could range from early lead identification to late-stage optimization phase. Will be a member of multi-disciplinary drug discovery teams of medicinal chemists, DMPK, structural biologists and pharmacologists, where opportunities to impact will abound.
Experience with Molecular Modeling domains is required, as applied to compound design and optimization such as Pharmacophore Analyses, Library Design, virtual HTS, Diversity/Similarity Analyses, Scaffold Hopping. A demonstrated success with an overall application of several integrated approaches (ex: ML derived predictions, Modeling SBD/ LBD) to progressing compound design contextual in drug discovery, is highly desirable and will serve as a strong bonus to consideration. Publications, posters or documented examples would be helpful.
Preference also given to candidates with previous roles in biotech/pharma companies and capable of independently driving forward Drug Discovery projects involving Structure Based Design including, but not limited to, target protein flexibility considerations.
Exposure to harnessing large datasets including public domain datasets of chemistry related to various targets and/or chemogenomic nature would be an asset.
Knowledge about computational technologies for the assessment of early-stage targets (ex: druggability) is helpful but not essential. Familiarity with well-known commercial molecular modeling software suites is also desirable such as Schrodinger, CCG or Open Eye.
Your Contributions (include, but are not limited to):
Your Contributions (include, but are not limited to):
  • Projects could range from early lead identification to the late-stage optimization of advanced projects. In particular, you will be able to join and potentially lead the development of an in-silico modeling platform within the Chemistry Department. As an active contributing member of multi-disciplinary drug discovery projects comprised of Medicinal Chemists, Biologists, DMPK & toxicologists there will be enormous opportunities to impact projects, as well as ample collaboration opportunities to share and learn from similar ML-derived predictive modeling efforts in other Neurocrine's R&D functions
  • Expertise with structure-based design methods to support drug discovery projects in the industry
  • Contributes to the Computational Chemistry group's efforts in implementing computational chemistry and/or cheminformatics methods for expediting the Design-Make-Test-Analyze discovery cycle
  • Generates productive hypotheses from Protein-ligand docking, for project teams that leads to successful compound optimization in subsequent design cycles
  • Develops advanced Machine Learning/AI in-silico models for numerous DMPK/in-vitro Biology endpoints, for front-loading projects with appropriate predictive information, to enable more efficient MPO analyses
  • Takes ownership of predictive platform and provides maintenance including regular updates
  • Facilitate the medicinal chemists design new compounds with desirable optimizable properties that are predicted using cutting-edge computational technologies integrating structural, chemical and biological data
  • Employs computational platform to make significant contribution to rationalizing experimental results, SAR evolution, and generating impactful ideas that are aligned with team's strategy to progress compounds forward in projects
  • Plays a lead role in identifying and/or developing/refining new computational methods, in tandem with self-interest and relevance to projects, to help augment Neurocrine's Computational Chemistry platform for Drug Discovery
  • Participates in a multidisciplinary team committed to the continuous improvement of the lead optimization process as well as the expeditious identification of development compounds.
  • Engages stakeholders from multiple Research functions to deliver and/or exchange key results
  • May contribute to the assessment of early-stage projects to help determine its entry into portfolio
  • Keeps abreast of developments of related interest through literature and advises project teams and/or computational chemistry group of innovation that could be harnessed into improving our platform
  • Aligned with strategies emanating from project teams, department and computational chemistry group
  • Conducive to sharing knowledge, practices, and work details, as needed, with teams and receptive to incorporating ideas from teams for continuous enrichment to best practices
  • Other duties as assigned

Requirements:
  • BS/BA degree in Chemistry and 5+ years of relevant experience, including familiarity utilizing any or all of the following: Machine Learning/AI based predictive modeling, Cheminformatics, Protein-Ligand modeling is preferred OR
  • MS/MA degree in Chemistry and 3+ years of similar experience noted above OR
  • 3+ years of post-Ph.D experience preferred
  • Recognizes fundamental anomalies in data points and identifies issues in experiments / processes
  • Begins to understand how to think outside of the technical process and consider the impact decisions will have on the broader scientific goals
  • Strong knowledge of scientific discipline
  • Good knowledge of scientific principles, methods and techniques
  • Good knowledge and demonstrated ability working with a variety of laboratory equipment/tools
  • Strong computer skills
  • Good problem-solving, analytical thinking skills
  • Detail oriented
  • Ability to meet deadlines
  • Excellent communication skills with the ability to collaborate with cross-functional scientists

The pay you should reasonably expect to receive is $53.26 - $77.21 per hour.
Decisions depend on various factors, such as primary work location, complexity and responsibility of role, job duties/requirements, and relevant experience and skills.
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Requirements:
Neurocrine Biosciences is an EEO/Disability/Vets employer.
We are committed to building a workplace of belonging, respect, and empowerment, and we recognize there are a variety of ways to meet our requirements. We are looking for the best candidate for the job and encourage you to apply even if your experience or qualifications don't line up to exactly what we have outlined in the job description.

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