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Delivering data science, data engineering, & AI solutions.

Data & Cloud Engineering Consultant

$100k – $150k • No equity
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This is a technical & consulting role within our data science team. The role is to design and develop solutions for various organizations looking to implement tools, software, and processes that support machine learning and AI initiatives using data engineering, DevOps, and MLOps best practices.

This role uses your abilities in cloud development, automation, data engineering, automation and streamlining IT infrastructure processes for organizations in healthcare, life sciences, biotech, semiconductors, public sector, manufacturing, agriculture, and other industries. Opportunity to expand and develop data science & AI algorithm skills are available.

SFL Scientific is a data science consulting and professional services company, providing a broad range of solutions in data engineering, machine learning, and Artificial Intelligence. We provide strategy, prototype, integrate, and manage sophisticated AI solutions by leveraging emerging technology. With a globally connected network of technology partners, we support our clients by helping them create powerful data products, help organizations capture the value of emerging data capabilities, and bring the lessons learned through that work to our internal development processes.

Our team solves complex and R&D type problems, tackling and helping organizations solve some of their most complex challenges with mathematics, data science, data engineering, and emerging technology. We are platform agnostic and are committed to providing the best technical solutions for each client and problem. Join us in Boston to build a technical career through consulting and professional services.


- Work with clients and their teams to design, develop, and deploy architectures for machine learning & automation applications such as ETL functions, compute infrastructure, parallelization, and optimization of DevOps procedures.

- Collaborate with colleagues to support and improve architecture, systems, processes, standards, and tools.

- Support and enhance data architecture, data instrumentation, define database schemas (Graph DB, SQL, NoSQL), create ETL pipe­lining, generate reports/insights, guide algorithm scalability and deployment.

- Participate in architectural discussions to ensure solutions are designed for successful deployment, security, and high availability in the cloud.

- Write and maintain code for automating the creation of scalable/resilient systems/infrastructure.

- Educate/mentor data scientists and teams on best practices.

General Requirements:

- Bachelor’s degree in physics, math, computer science, statistics, or related quantitative field, or equivalent experience.

- Knowledge of the various services and capabilities of computing platforms (AWS/Azure/GCP).

- Expertise with AWS such as IAM, EC2, EBS, ELB, RDS, S3, Redshift, CloudWatch, Lambda.

- Expertise with Azure, and similar functionality services as above.

- Experience managing and supporting Docker, Kubernetes, Spark, Dask, Flask, CI/CD services.

- Shell, Python, Powershell experience is a must.

- Strong verbal & written communication skills and demonstrated ability of working with outside firms as a consultant.

- Understanding of agile and other development processes and methodologies.

- Experience with provisioning and configuration management tools; Puppet, Ansible, Chef, Terraform, etc.

Preferred Qualifications:

- AWS/Azure Certifications a plus (AWS/Azure Certified: SysOps Administrator, DevOps Engineer, Solutions Architect).

- Strong knowledge and understanding of CI/CD processes and tools (e.g., Jenkins).

- Master's or Ph.D degree in Physics, Math, Computer Science, Statistics, or related quantitative field.

Medical, Dental, & Vision


Parental Leave

Unlimited Vacation Policy

Certifications & Conferences

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