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Director Chemical Engineering Data Science Jobs in Washington

Blend360

Director, AI Engineering (Data Science)

Columbia, MD · On-site +1

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Mentor, and manage AI/ML engineers, senior data scientists, and MLOps engineers-setting performance ... Direct experience with industry datasets in marketing & media (DSP/DMP logs, ad impression data ...

Blend360

Director, AI Engineering (Data Science)

Columbia, MD

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Mentor, and manage AI/ML engineers, senior data scientists, and MLOps engineers-setting performance ... Direct experience with industry datasets in marketing & media (DSP/DMP logs, ad impression data ...

Gartner

Director, Data Science

Arlington, VA · Remote

  • Medical

  • Retirement

  • PTO

The Director, Data Science will lead efforts across personalization, recommendation systems, and ... Collaborate with engineering, product, UX, and business leaders to prioritize ideas, launch MVPs ...

Total Wine & More

Director, Data Science

Bethesda, MD · On-site

Total Wine & More is seeking a Director of Data Science to join our Technology team in our Bethesda, MD office. This role will lead multiple data science team members with a significant portfolio of ...

Tulk LLC

Data Science SME Mid

Fort Belvoir, VA · On-site

$115K - $157K/yr

... directed by the customer. * Education: A bachelor's degree from an accredited (i.e., regional ... Programming, Statistics, or Data Visualization). * Education: Department of Defense (DoD) Basic ...

Bigbear.ai

Data Scientist, Lead

Washington, DC · On-site

$142K - $228K/yr

Bachelor's degree in data science, data engineering, mathematics, or another related field * Minimum of 3 years of experience conducting analysis using data science or engineering (an additional 4 ...

Cruz Associates Inc

Chemical Engineer

Indian Head, MD · On-site

... Chemical Engineer . The job location is at the Naval Surface Warfare Center in Indian Head, MD ... Ability to use intermediate engineering/scientific techniques, requirements, methods, sources, and ...

SOSi

Data Scientist III

Washington, DC · On-site

This role is responsible for applying data science, machine learning, and data engineering techniques to enhance enterprise security monitoring, detection, threat hunting, user and entity behavior ...

Tulk LLC

Data Science SME Senior

Fort Belvoir, VA · On-site

$120K - $171K/yr

... directed by the customer. * Education: A bachelor's degree from an accredited (i.e., regional ... Programming, Statistics, or Data Visualization). * Education: Department of Defense (DoD) Basic ...

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

Director Chemical Engineering Data Science information

What does a director chemical engineering data science do?

A Director of Chemical Engineering Data Science leads teams that apply data science principles to chemical engineering challenges, such as optimizing processes, improving safety, and driving innovation. This role involves overseeing data-driven projects, collaborating with engineers and data scientists, and ensuring that advanced analytics and machine learning are effectively used in chemical engineering operations. The director also plays a strategic role in shaping data initiatives and aligning them with organizational goals.

How does a director chemical engineering data science typically collaborate with cross-functional teams to drive innovation?

A Director of Chemical Engineering Data Science frequently works alongside R&D scientists, process engineers, IT specialists, and business strategists to bridge the gap between data analytics and chemical engineering processes. This role involves leading data-driven projects, translating complex technical findings into actionable insights, and ensuring that data science initiatives align with organizational goals. Effective collaboration is essential, as the director often facilitates communication across departments, mentors interdisciplinary teams, and champions the adoption of new technologies to enhance innovation and operational efficiency.

What are the key skills and qualifications needed to thrive as a director chemical engineering data science, and why are they important?

To thrive as a Director of Chemical Engineering Data Science, you need advanced expertise in chemical engineering principles, data science methodologies, and a graduate degree in a related field. Proficiency with statistical analysis software (e.g., Python, R), machine learning platforms, and familiarity with process simulation tools are typically required, along with relevant certifications in data science or engineering management. Strong leadership, strategic thinking, and effective communication skills help drive cross-functional teams and translate complex data into actionable business insights. These skills and qualities are crucial for leveraging data-driven solutions to optimize chemical processes, enhance innovation, and achieve organizational objectives.

What is the difference between Director Chemical Engineering Data Science vs Chemical Engineer?

AspectDirector Chemical Engineering Data ScienceChemical Engineer
Required CredentialsAdvanced degrees (Master's/PhD), leadership experience, data science certificationsBachelor's or Master's in Chemical Engineering, engineering licensure often preferred
Work EnvironmentStrategic leadership, cross-departmental collaboration, data-driven decision makingDesign, develop, and optimize chemical processes in manufacturing or R&D
Employer & Industry UsageTech companies, large manufacturing firms, R&D organizationsChemical plants, pharmaceuticals, energy, and manufacturing industries

The main difference is that the Director Chemical Engineering Data Science focuses on strategic leadership and data-driven insights in chemical engineering, often requiring advanced degrees and data science expertise. In contrast, a Chemical Engineer is primarily involved in designing and operating chemical processes, with a focus on technical engineering skills and practical application.

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 Director Chemical Engineering Data Science jobs in Washington?

For Director Chemical Engineering Data Science jobs in Washington, the most frequently searched job titles are:

What job categories do people searching Director Chemical Engineering Data Science jobs in Washington look for?

The top searched job categories for Director Chemical Engineering Data Science jobs in Washington are:

What cities in Washington are hiring for Director Chemical Engineering Data Science jobs?

Cities in Washington with the most Director Chemical Engineering Data Science job openings:

Director Chemical Engineering Data Science jobs near you
Infographic showing various Director Chemical Engineering Data Science job openings in Washington as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 14% Part Time, and 5% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Director, AI Engineering (Data Science)

Blend360

Columbia, MD • On-site, Remote

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 28 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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