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Associate Computer Science Jobs in Lynn, MA (NOW HIRING)

Bayer

Associate Dir, Full Stack Data Scientist

Cambridge, MA · On-site +1

$64K - $65K/yr

The purpose of the Associate Director is to lead and deliver cross-functional Data Science ... Minimum of a Master's Degree in Statistics, Mathematics, Informatics, Computer Sciences, ML Ops ...

Bayer

Associate Dir, Full Stack Data Scientist

Cambridge, MA · On-site

$64K - $65K/yr

The purpose of the Associate Director is to lead and deliver cross-functional Data Science ... Minimum of a Master's Degree in Statistics, Mathematics, Informatics, Computer Sciences, ML Ops ...

Pathstone

Associate, Technology

Boston, MA

The Associate in Technology will provide technical assistance and answers to users' questions ... Education Bachelor's degree in Computer Science or related field preferred. Work Experience At ...

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All JobsAssociate Computer Science JobsAssociate Computer Science Jobs in Lynn, MA

Associate Computer Science information

See Lynn, MA salary details

$9

$19

$32

How much do associate computer science jobs pay per hour?

As of Jul 14, 2026, the average hourly pay for associate computer science in Lynn, MA is $19.61, according to ZipRecruiter salary data. Most workers in this role earn between $15.62 and $20.82 per hour, depending on experience, location, and employer.

What professions make 200,000 a year without a degree?

In the tech industry, roles such as software sales executives, cloud solutions architects, and certain cybersecurity specialists can earn $200,000 or more annually without a traditional degree, often relying on extensive experience, certifications, and technical skills. Sales positions in technology companies and specialized IT consulting also have high earning potential without requiring a formal degree.

What jobs pay 4000 a week without a degree?

In the field of computer science, roles such as freelance software developers, cybersecurity consultants, or cloud engineers can potentially earn $4,000 or more weekly through project-based work or contracts, often requiring strong technical skills, certifications, and experience. These positions typically involve remote work, self-employment, or contract arrangements rather than traditional employment, and income depends on skill level, client base, and project scope.

What are the key skills and qualifications needed to thrive as an Associate in Computer Science, and why are they important?

To thrive as an Associate in Computer Science, you need foundational knowledge in programming, algorithms, data structures, and typically a bachelor’s degree in computer science or a related field. Familiarity with programming languages like Python, Java, or C++, experience with version control systems such as Git, and understanding of databases are commonly required. Strong analytical thinking, problem-solving skills, and the ability to collaborate effectively with others help you stand out in this role. These competencies ensure you can successfully contribute to software development projects, solve technical challenges, and support team goals in a dynamic technology environment.

What is the difference between Associate Computer Science vs Computer Programmer?

AspectAssociate Computer ScienceComputer Programmer
Required CredentialsAssociate's degree in Computer Science or related fieldTypically a bachelor's degree or coding bootcamp certification
Work EnvironmentEntry-level, team-based projects in tech companies, startups, or IT departmentsWriting, testing, and debugging code in various programming languages
Employer & Industry UsageCommon in tech firms, government agencies, and educational institutionsWidely used across software companies, finance, and tech industries

The main difference is that an Associate Computer Science focuses on foundational knowledge and may involve broader IT tasks, while a Computer Programmer specializes in coding and software development. Both roles often require similar educational backgrounds, but their daily tasks and career paths differ.

What types of projects and technologies can an Associate Computer Science professional expect to work on in their first year?

As an Associate Computer Science professional, you will often be assigned to entry-level projects such as developing or maintaining software applications, testing code, or assisting with database management. You'll likely work with common programming languages like Java, Python, or C++, and may be introduced to collaborative tools such as version control systems (e.g., Git). The team environment typically includes regular code reviews and mentorship from senior engineers, providing opportunities to learn best practices and develop your technical skills. Over time, you'll gain exposure to more complex tasks and technologies as you build your experience.

What is an Associate Computer Science professional?

An Associate Computer Science professional typically holds an associate degree in computer science or a related field and works in entry-level positions within the tech industry. They are responsible for assisting with software development, troubleshooting, maintaining computer systems, and supporting IT teams. These professionals often work under the supervision of more experienced engineers or developers and may contribute to coding, testing, and basic technical support. The role is a great starting point for those looking to build a career in technology and can lead to more advanced opportunities with experience and further education.

Is an Associates in computer science useful?

An associate's degree in computer science provides foundational knowledge of programming, algorithms, and systems, which can help qualify for entry-level roles such as support technician or junior developer. It can also serve as a stepping stone to a bachelor's degree or specialized certifications, increasing job opportunities in the tech field.

What can you do with an associate's degree in computer science?

An associate's degree in computer science prepares individuals for entry-level roles such as computer support specialist, help desk technician, or network technician. It provides foundational skills in programming, troubleshooting, and basic networking, often enabling employment in IT departments or technical support environments.
What are the most commonly searched types of Computer Science jobs in Lynn, MA? The most popular types of Computer Science jobs in Lynn, MA are:
What job categories do people searching Associate Computer Science jobs in Lynn, MA look for? The top searched job categories for Associate Computer Science jobs in Lynn, MA are:
What cities near Lynn, MA are hiring for Associate Computer Science jobs? Cities near Lynn, MA with the most Associate Computer Science job openings:
Associate Computer Science jobs near you
Infographic showing various Associate Computer Science job openings in Lynn, MA as of July 2026, with employment types broken down into 1% As Needed, 68% Full Time, 29% Part Time, 1% Temporary, and 1% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution, with an average salary of $40,791 per year, or $19.6 per hour.
Associate Principal Scientist, Biologics AI

Associate Principal Scientist, Biologics AI

AstraZeneca

Cambridge, MA • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

This job post has expired today. Applications are no longer accepted.

AstraZeneca rating

8.4

Company rating: 8.4 out of 10

Based on 44 frontline employees who took The Breakroom Quiz

18th of 74 rated pharmaceutical

Job description

About the Role
We are seeking an experienced and visionary Associate Principal Scientist to lead Biologics AI innovation at AstraZeneca's US R&D centers in Waltham, MA or Gaithersburg, MD. This is a high-impact scientific leadership role accountable for defining and executing the AI strategy that integrates state-of-the-art machine learning with wet-lab discovery to accelerate biologics engineering and enable next-generation biotherapeutics. You will set technical direction, own delivery across multiple programs, and shape data generation at scale-working across computational and experimental functions and with global partners to translate AI into robust, reproducible advances in discovery.
Key Responsibilities
  • Strategic leadership and vision: Define and drive the AI strategy for biologics discovery and engineering, setting priorities and roadmaps that integrate AI and wet-lab capabilities and deliver measurable impact on pipeline goals.
  • Program ownership: Lead multiple cross-functional discovery initiatives from problem framing through deployment, ensuring rapid translation of computational insights into experimental design and decision-making.
  • Advanced ML innovation: Architect, develop, and guide application of cutting-edge models-protein language models, structure-informed and geometric methods, de novo/protein design, and multi-modal learning that fuses sequence, structure, and biological activity data-to solve high-value scientific problems.
  • AI-wet-lab integration at scale: Establish closed-loop design-build-test-learn workflows with experimental teams, formalizing feedback cycles, uncertainty quantification, and active learning to improve model reliability and throughput.
  • Data strategy and governance: Set standards for high-quality data generation, curation, and metadata; partner with wet-lab leaders to design assays and campaigns that maximize ML utility and reproducibility; influence data platform evolution in collaboration with informatics and engineering.
  • End-to-end ML lifecycle leadership: Oversee and improve processes across data pipelines, model development, validation, deployment, monitoring, and continuous improvement, including best practices for reproducibility, documentation, and scientific rigor.
  • Technical mentorship and team development: Mentor and upskill scientists across AI/ML and experimental domains; provide day-to-day technical guidance and contribute to recruitment and development of a high-performing team.
  • Stakeholder influence and communication: Communicate strategy, progress, risk, and scientific insights to senior stakeholders; influence portfolio decisions and advocate for AI-enabled approaches internally and with external partners.
  • External scientific leadership: Drive publications, patents, and external visibility; represent AstraZeneca in collaborations and at scientific venues; evaluate and integrate emerging methods and tools.

Required Qualifications
  • Education and experience: PhD in computer science, machine learning, bioinformatics, computational biology, physics, chemistry, mathematics, engineering, or a related quantitative field, with typically 8+ years of relevant post-degree experience in academia and/or industry; or a Master's with 12+ years of relevant experience.
  • Domain impact in biologics AI: Demonstrated track record applying AI/ML to proteins, antibodies, or related biologics, with clear examples of methods translated into experimental outcomes, platform capabilities, or pipeline decisions.
  • Deep technical expertise: Hands-on leadership in developing and deploying advanced ML (deep learning, generative models, structure-aware and geometric methods, sequence/structure multi-modal models) for protein sequence modeling, structure-informed prediction, de novo design, or biologics optimization.
  • Closed-loop integration: Proven success establishing iterative computational-experimental cycles (e.g., active learning, design-build-test-learn), including designing experiments to interrogate model predictions and improve data/model quality.
  • Lifecycle and systems: Experience leading the full ML lifecycle at scale-data design and preprocessing, model architecture, training/evaluation, deployment, monitoring, and maintenance-using modern ML frameworks (e.g., PyTorch, TensorFlow) and software engineering best practices.
  • Data and platforms: Experience with cloud-based ML environments and scalable data workflows; ability to specify requirements and partner with data engineering/IT to evolve production ML systems that support discovery at scale.
  • Cross-functional leadership: Strong record of influencing and delivering in matrixed, multidisciplinary environments, bridging AI scientists, computational biologists, protein engineers, and wet-lab teams across sites.
  • Scientific communication: Excellent communication skills with the ability to synthesize complex technical concepts for diverse audiences and to shape scientific and portfolio decisions.
  • Innovation and delivery: Evidence of scientific innovation and impact through publications, patents, platform creation, or deployment of AI methods that materially improved experimental or business outcomes.

Preferred Qualifications
  • Protein and antibody engineering: Experience with antibody/nanobody/protein engineering, including de novo design and multi-objective optimization for developability, stability, and functional performance.
  • Advanced methodologies: Expertise with generative models (e.g., diffusion, autoregressive LMs), geometric deep learning/graph neural networks, Bayesian optimization, uncertainty quantification, and active learning for guided experimentation.
  • Multi-modal learning: Experience integrating heterogeneous data types (sequence, structure, biophysics/biochemistry assays, high-throughput binding/functional data, bioprocess/developability metrics) into unified models.
  • Productionization and MLOps: Experience leading deployment of scientific software/ML models into production discovery workflows, including model monitoring, versioning, and compliance with governance standards.
  • Data generation strategy: Demonstrated ability to design or refine assay strategies and experimental campaigns to maximize downstream ML performance and data reuse, including metadata standards and FAIR principles.
  • People and project leadership: Prior experience leading scientists and managing complex projects or collaborations; ability to set goals, delegate effectively, and deliver against timelines.
  • External profile: Strong external scientific presence (peer-reviewed publications, patents, invited talks, open-source contributions, or community standards).

Why Join Us?
As part of AstraZeneca's dynamic US biologics R&D community, you will play a critical role in shaping the future of AI-driven biologics discovery and engineering. Collaborating across cutting-edge computational and experimental teams, you'll drive innovation that brings transformative medicines to patients around the world. You will be supported by a collaborative, inclusive, and empowering environment, with unparalleled opportunities for scientific impact and personal growth.
The annual base pay for this position ranges from $144,648.80 - $216,973.20. Our positions offer eligibility for various incentives-an opportunity to receive short-term incentive bonuses, equity-based awards for salaried roles and commissions for sales roles. Benefits offered include qualified retirement programs, paid time off (i.e., vacation, holiday, and leaves), as well as health, dental, and vision coverage in accordance with the terms of the applicable plans.
Date Posted
07-Jul-2026
Closing Date
06-Jul-2026
Our mission is to build an inclusive environment where equal employment opportunities are available to all applicants and employees. In furtherance of that mission, we welcome and consider applications from all qualified candidates, regardless of their protected characteristics. If you have a disability or special need that requires accommodation, please complete the corresponding section in the application form.

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