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Ml Data Associate Jobs (NOW HIRING)

iSoftStone

Associate AI/ML Developer

White Plains, NY

$20/hr

iSoftStone, Inc. is seeking an Associate AI/ML Developer to join our Team In New York, NY, Seattle ... Recently graduated from, a degree/certificate program in Computer Science, AI/ML, Data Science ...

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Lantern

Data Scientist

Dallas, TX

Azure Data Scientist Associate), or Databricks ML Data Scientist Certifications a plus * Experience with GitHub or Azure DevOps * Prior consulting and business development experience a plus.

Leidos

Data Scientist

Fort George G Meade, MD

$107K - $195K/yr

Associate's degree with 12 years of relevant experience may be considered. * Other degrees with strong coursework in advanced math, statistics, AI/ML, computer science, or data mining, or relevant ...

Lantern

Data Scientist

Dallas, TX · On-site

Azure Data Scientist Associate), or Databricks ML Data Scientist Certifications a plus * Experience with GitHub or Azure DevOps * Prior consulting and business development experience a plus.

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Ml Data Associate information

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How much do ml data associate jobs pay per year?

As of Jun 16, 2026, the average yearly pay for ml data associate in the United States is $68,039.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,000.00 and $59,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an ML Data Associate, and why are they important?

To thrive as an ML Data Associate, you need strong analytical skills, attention to detail, and a solid understanding of data annotation or labeling, often supported by a degree in a technical field. Familiarity with data labeling tools, basic programming (such as Python), and experience working with machine learning platforms are typically required. Excellent communication, problem-solving abilities, and the capacity to work efficiently in teams are important soft skills. These skills ensure high-quality, accurately labeled datasets that are essential for training effective machine learning models.

What are ML Data Associates?

ML Data Associates are professionals who support machine learning projects by preparing, labeling, and validating data used to train and evaluate algorithms. They often work with large datasets, ensuring data quality and accuracy, and may use specialized tools to annotate images, text, or audio. Their work is essential for enabling machine learning models to learn from high-quality, well-structured data, and they often collaborate with data scientists and engineers to optimize data pipelines.

What is the difference between Ml Data Associate vs Data Analyst?

AspectML Data AssociateData Analyst
Required CredentialsTypically a degree in computer science, data science, or related field; familiarity with machine learning conceptsUsually a degree in statistics, mathematics, or business analytics; strong Excel and data visualization skills
Work EnvironmentTech companies, AI startups, or organizations focusing on machine learning projectsBusiness, finance, marketing, and consulting firms analyzing data for insights
Employer & Industry UsageUsed in industries developing AI models, machine learning pipelines, and data infrastructureCommon across industries for reporting, trend analysis, and strategic decision-making

While both roles involve working with data, ML Data Associates focus on preparing and managing data specifically for machine learning models, whereas Data Analysts interpret data to generate business insights. The roles overlap in data handling skills but differ in their end goals and technical focus.

What are some common challenges faced by ML Data Associates when labeling complex datasets, and how can they be effectively addressed?

ML Data Associates often encounter challenges with ambiguous data, inconsistent labeling guidelines, or rapidly evolving project requirements. To address these, it's important to maintain open communication with data scientists and project leads, ask clarifying questions, and participate in regular calibration sessions to ensure consistency. Utilizing annotation tools efficiently and staying up-to-date with best practices can also help manage complexity and improve label quality. Collaboration and feedback within the team are key to overcoming these challenges and ensuring high-quality datasets.
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Ml Data Associate jobs near you

PhD Scientist, Drug Discovery Data | AI/ML

StaffRight Associates, LLC

Manhattan, NY • Hybrid

Other

Posted 7 days ago

Job description

Preface

The architectural integrity of global investment and technology research relies on the seamless convergence of Computational Drug Discovery and rigorous computational execution. Within this domain, where the synthesis of complex data and high-performance systems is the primary objective, the necessity for first-principles mastery extends beyond the laboratory and into the operational nucleus of the organization.

StaffRight Associates is seeking an elite professional to join the ML Data team at a world-class firm dedicated to the advancement of computational excellence. This role demands a candidate who possesses the intellectual pedigree required to navigate the complex challenges of a research-intensive environment. By bridging specialized technical awareness with proactive problem-solving, the successful candidate will ensure the structural alignment of the firm’s strategic mission with its technical execution.

The Mission

StaffRight Associates is recruiting for a Scientist, Drug Discovery Data for AI/ML. As a vital catalyst within a premier organization, your mission is to decouple systemic friction from analytical progress, allowing the firm’s leadership to maintain a singular focus on the acceleration of Molecular Dynamics Simulation and Atomistic Modeling. You will be tasked with the sophisticated management of Scientific Dataset Curation and Analysis, transforming abstract organizational needs into formalized, actionable results. This role requires a high degree of technical literacy to effectively support a team leveraging proprietary architectures and sophisticated algorithms to revolutionize Precision Drug Design.

Core Technical Objectives

  • Orchestrate Systemic Workflows: Formalize and execute complex protocols and high-stakes technical workflows to ensure continuous operational flow for the ML Data team.

  • Synthesize Complex Data: Identify, curate, and analyze multifaceted chemical and biological datasets, distilling information into coherent frameworks that support AI/ML model development.

  • Optimize Operational Frameworks: Validate and process intricate documentation and technical requirements with meticulous attention to detail and systemic accuracy.

  • Engineer Multi-Project Solutions: Independently manage a diverse portfolio of concurrent projects, applying a proactive Goal-Execution-Mapping (GEM) approach to solve emergent bottlenecks in data strategy.

  • Facilitate Elite Communication: Serve as a discreet and articulate interface between the machine learning committee and interdisciplinary stakeholders, maintaining the highest standards of professional integrity.

Candidate DNA

  • Architectural Philosophy: A mindset rooted in efficiency and resilience, with the ability to navigate a hybrid, high-pressure environment without supervision.

  • Resourceful Problem-Solving: A proven track record of autonomous execution, demonstrating the ability to anticipate systemic bottlenecks before they impact the broader workflow.

  • Communication Precision: Exceptional interpersonal skills characterized by clarity, discretion, and the ability to interact with elite scientific and business minds.

  • Functional Versatility: A generalist mindset capable of pivoting between rigorous execution and technical inquiry within a high-performance ecosystem.

Academic & Research Pedigree

  • Educational Foundation: A Ph.D. is required, ideally within Medicinal Chemistry, Pharmacology, Biology, or a related STEM discipline that provides a foundation for understanding molecular behavior.

  • Domain Expertise: Significant professional engagement within pharmaceutical or biotech sectors, specifically involving hands-on laboratory experience and drug discovery projects, is highly advantageous.

  • Quantitative Literacy: Comfort with the mathematical and operational rigor inherent in a firm focused on supercomputing, Python-based data manipulation, and high-speed data processing.

Partnering with StaffRight Associates

At StaffRight Associates, we operate at the intersection of technical synthesis and structural alignment. We don’t just match resumes to keywords; we map your engineering DNA, your architectural philosophy, and your approach to system resilience to the most sophisticated STEM challenges in the industry.

When you partner with us, you are engaging with an elite team that speaks your language and understands the nuances of high-stakes innovation. We are committed to placing elite talent where their technical contributions drive systemic impact.

Apply