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Remote Chemical Engineering Data Science Jobs in Washington

AVIAN, LLC

Data Engineer

Reston, VA · On-site +1

$119K - $143K/yr

Computer Science * Computer / Electrical Engineering or related field * Data Science or related ... This position has an on-site requirement and is not eligible for fully remote candidates. At Level ...

Level Up Llc

Data Engineer

Reston, VA · On-site +1

$119K - $143K/yr

Computer Science * Computer / Electrical Engineering or related field * Data Science or related ... This position has an on-site requirement and is not eligible for fully remote candidates. At Level ...

Maximus

Data Science Manager

VA · On-site +1

This is a remote role. Essential Duties and Responsibilities: - Oversee the ongoing developments ... Programming Languages: SQL, Python, R. - Cloud Based DBMS: Snowflake, Amazon RDS (Oracle, SQL ...

Gartner

Director, Data Science

Arlington, VA · Remote

Collaborate with engineering, product, UX, and business leaders to prioritize ideas, launch MVPs, iterate rapidly, and deliver measurable business value. * Lead a team of data scientists, driving ...

Gartner

Director, Data Science

Arlington, VA · Remote

Collaborate with engineering, product, UX, and business leaders to prioritize ideas, launch MVPs, iterate rapidly, and deliver measurable business value. * Lead a team of data scientists, driving ...

Deloitte

AI and Data Science Engineer III

Mclean, VA · On-site +1

$115K - $139K/yr

AI and Data Science Engineer III Position Summary Our Deloitte Human Capital team transforms ... Deliver governed datasets and feature engineering and serving patterns for machine learning ...

Varsity Tutors

Data Science Tutor

Washington, DC · Remote

$40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery: Deep knowledge of statistical ... programming, hypothesis testing, and communication of data-driven insights. Ability to explain ...

Varsity Tutors

Data Science Tutor

Bowie, MD · Remote

$40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery: Deep knowledge of statistical ... programming, hypothesis testing, and communication of data-driven insights. Ability to explain ...

Varsity Tutors

Data Science Tutor

College Park, MD · Remote

$40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery: Deep knowledge of statistical ... programming, hypothesis testing, and communication of data-driven insights. Ability to explain ...

Varsity Tutors

Data Science Tutor

Rockville, MD · Remote

$40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery: Deep knowledge of statistical ... programming, hypothesis testing, and communication of data-driven insights. Ability to explain ...

Varsity Tutors

Data Science Tutor

Leesburg, VA · Remote

$40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery: Deep knowledge of statistical ... programming, hypothesis testing, and communication of data-driven insights. Ability to explain ...

Varsity Tutors

Data Science Tutor

Fairfax, VA · Remote

$40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery: Deep knowledge of statistical ... programming, hypothesis testing, and communication of data-driven insights. Ability to explain ...

Varsity Tutors

Data Science Tutor

Alexandria, VA · Remote

$40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery: Deep knowledge of statistical ... programming, hypothesis testing, and communication of data-driven insights. Ability to explain ...

Varsity Tutors

Data Science Tutor

Laurel, MD · Remote

$40/hr

What We Look For In a Data Science Tutor * Advanced Subject Mastery: Deep knowledge of statistical ... programming, hypothesis testing, and communication of data-driven insights. Ability to explain ...

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All JobsChemical Engineering Data Science JobsRemote Chemical Engineering Data Science JobsRemote Chemical Engineering Data Science Jobs in Washington

Remote Chemical Engineering Data Science information

What is the difference between Remote Chemical Engineering Data Science vs Remote Chemical Engineering?

AspectRemote Chemical Engineering Data ScienceRemote Chemical Engineering
Required CredentialsBachelor's or higher in Chemical Engineering, Data Science, or related fields; knowledge of programming and data analysisBachelor's or higher in Chemical Engineering; engineering licensure may be preferred
Work EnvironmentPrimarily remote, involving data analysis, modeling, and software toolsRemote or on-site, focusing on process design, safety, and plant operations
Employer & Industry UsageTech companies, consulting firms, or R&D departments integrating data scienceManufacturing, oil & gas, pharmaceuticals, and chemical plants

Remote Chemical Engineering Data Science combines chemical engineering principles with data analysis skills, often working remotely on modeling and data-driven decision-making. In contrast, Remote Chemical Engineering focuses on process design and plant operations, which may involve on-site work. Both roles require a chemical engineering background but differ in technical focus and work environment.

How do remote chemical engineering data scientists typically collaborate with cross-functional teams?

Remote chemical engineering data scientists often work closely with R&D, process engineering, and IT teams to analyze complex datasets and develop data-driven solutions. Collaboration is facilitated through virtual meetings, shared digital platforms, and clear documentation. Regular communication and project management tools help coordinate tasks, track progress, and ensure that insights are effectively integrated into engineering projects. Building strong relationships remotely can be a challenge, but proactive communication and participation in team discussions are key to successful collaboration.

What is a Remote Chemical Engineering Data Scientist?

A Remote Chemical Engineering Data Scientist is a professional who applies data science techniques, such as machine learning and statistical analysis, to chemical engineering problems while working outside a traditional office setting. They analyze data from chemical processes, develop predictive models, and help optimize production, often collaborating with teams virtually. This role requires a strong foundation in chemical engineering principles, programming skills, and experience with data analytics tools. Working remotely offers flexibility but also demands excellent communication and self-management skills.

What are the key skills and qualifications needed to thrive as a Remote Chemical Engineering Data Scientist, and why are they important?

To excel as a Remote Chemical Engineering Data Scientist, you need a strong background in chemical engineering principles, data analysis, and statistical modeling, often supported by a degree in engineering or data science. Proficiency in programming languages like Python or R, experience with machine learning frameworks, and familiarity with process simulation tools are typically required. Exceptional problem-solving skills, communication, and the ability to collaborate virtually make candidates stand out in this remote environment. These capabilities are vital for transforming complex chemical process data into actionable insights and driving innovation from a distance.
What are the most commonly searched types of Chemical Engineering Data Science jobs in Washington? The most popular types of Chemical Engineering Data Science jobs in Washington are:
What are popular job titles related to Remote Chemical Engineering Data Science jobs in Washington? For Remote Chemical Engineering Data Science jobs in Washington, the most frequently searched job titles are:
What job categories do people searching Remote Chemical Engineering Data Science jobs in Washington look for? The top searched job categories for Remote Chemical Engineering Data Science jobs in Washington are:
What cities in Washington are hiring for Remote Chemical Engineering Data Science jobs? Cities in Washington with the most Remote Chemical Engineering Data Science job openings:
Remote Chemical Engineering Data Science jobs near you
Infographic showing various Remote Chemical Engineering Data Science job openings in Washington as of June 2026, with employment types broken down into 80% Full Time, 12% Part Time, and 8% Contract. Highlights an 100% Remote job distribution.
Director, AI Engineering (Data Science)

Director, AI Engineering (Data Science)

Blend360

Columbia, MD • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 19 days ago

Job description

Company Description
Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. For more information, visit www.blend360.com.
Job Description
We are seeking a visionary and execution-oriented Director of AI Engineering to join our team. In this senior, client facing role, you will own the full lifecycle of AI model development, setting technical strategy and ensuring that cutting-edge machine learning solutions move from concept to production with business impact at their core.
With roots in data science and hands-on expertise in custom transformer architecture, you will bring both the credibility to lead technical teams. You will operate at the intersection of stakeholder management and deep technical execution and you should be equally comfortable presenting to a senior audience and reviewing model architecture with your team.
This is a high-impact, high-autonomyy role with significant organizational influence. You will define the AI roadmap, establish engineering best practices, and champion a culture of rigorous, reproducible, and responsible machine learning.
Strategic Leadership & Team Management
  • Define technical investments with business objectives
  • Mentor, and manage AI/ML engineers, senior data scientists, and MLOps engineers-setting performance expectations and a high-performance culture.
  • Partner with cross-functional leaders to prioritize initiatives, allocate resources, and measure organizational impact.
  • Establish engineering standards, code review practices, and model governance frameworks across the AI org.

Custom Transformer Architecture & Model Development
  • Serve as the technical authority on deep learning architecture-personally leading the design and development of custom transformer models for sequence modeling, customer propensity scoring, audience segmentation, and churn prediction.
  • Drive innovation in attention mechanisms, positional encodings, and tokenization strategies specifically suited to tabular, time-series, and event-stream data common in marketing and telecom.
  • Oversee adaptation and fine-tuning of foundation models (BERT, T5, TabTransformer, LLMs) for proprietary client datasets, ensuring domain-specific performance.
  • Champion reproducible experimentation and architectural decision documentation across the team.

Data Science & Applied Analytics
  • Oversee end-to-end data science workflows: problem framing, feature engineering, model development, validation, and production deployment.
  • Ensure statistical rigor in experimental design, causal inference, A/B testing, and offline/online evaluation frameworks.
  • Guide the team in building robust data pipelines for large-scale structured and unstructured datasets, including clickstream, CRM, ad telemetry, CDRs, and network KPIs.

Client & Executive Engagement
  • Lead technical discovery and solutioning with enterprise clients translating ambiguous business problems into well-scoped AI initiatives.
  • Present AI strategy, model results, and roadmap updates to C-suite and senior client stakeholders with clarity and executive presence.
  • Contribute to business development: support RFP responses, lead technical portions of client proposals, and help grow the AI engineering practice.

MLOps, Infrastructure & Governance
  • Establish production standards for model deployment, monitoring, drift detection, and automated retraining across cloud platforms (AWS SageMaker, GCP Vertex AI, Azure ML).
  • Drive adoption of MLOps best practices including CI/CD for ML, containerization (Docker/Kubernetes), and experiment tracking (MLflow, W&B, DVC).
  • Implement model governance, explainability, and responsible AI standards in compliance with client and regulatory requirements.

Qualifications
  • Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a closely related quantitative field; Ph.D. strongly preferred.
  • 10+ years of progressive experience in data science and machine learning, with at least 3-5 years in a people management or technical leadership role (Director, Sr. Manager, or Principal Engineer level).
  • Proven track record of leading high-performing AI/ML engineering teams in a fast-paced, client-facing or product environment.
  • Deep, hands-on expertise designing and training custom transformer architectures from scratch-not only fine-tuning pre-built checkpoints, but architecting novel attention mechanisms, embedding strategies, and model topologies.
  • Strong applied data science foundation: feature engineering, statistical modeling, causal inference, and experimental design across large-scale datasets.
  • Proficiency in Python and core ML/DL libraries: PyTorch (preferred), TensorFlow, HuggingFace Transformers, scikit-learn, XGBoost/LightGBM.
  • Direct experience with industry datasets in marketing & media (DSP/DMP logs, ad impression data, attribution pipelines, MMM) OR telecommunications (CDRs, network KPIs, subscriber behavior, churn datasets).
  • Command of SQL and large-scale data platforms: Spark, BigQuery, Snowflake, or Databricks.
  • Experience owning end-to-end MLOps: cloud deployment (SageMaker, Vertex AI, or Azure ML), monitoring, CI/CD for ML, and model governance.
  • Exceptional executive communication skills-able to translate complex model behavior into business language for C-suite and client audiences.

PREFERRED QUALIFICATIONS
  • Professional services experience across multiple client engagements or business units
  • Background in privacy-preserving ML: federated learning, differential privacy, or synthetic data generation-especially relevant in post-cookie marketing environments.
  • Knowledge of graph neural networks (GNNs) for social graph or network topology analysis in telecom contexts.
  • Published research or conference contributions (NeurIPS, ICML, KDD, RecSys, or industry equivalents) related to applied transformers, tabular deep learning, or domain-specific AI.
  • Experience with real-time inference and streaming ML pipelines (Kafka, Flink, or similar).
  • Demonstrated ability to build strategic partnerships with external clients, contributing to revenue growth or account expansion through technical leadership.
  • Deep experience with openai focused on embeddings
  • Experience building custom transformer models

Additional Information
The starting pay range for this role is $180,000 - $240,000. Actual compensation within the range will be dependent on several factors including but not limited to relevant experience, skills, certifications, training, and location. It is not typical for an individual to be hired at or near the top of the range and determining factors for compensation are considered for each individual circumstance. BLEND360 also offers a competitive benefits program to meet the health and financial well-being of our team and their families. You can look forward to a range of benefits including medical, dental, vision, 401K, PTO, paid holidays, commuter benefits, spending accounts, life insurance, disability coverage, and EAPs.

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