Data Scientist

Posted 7 Days Ago
New York, NY
144K-155K Annually
Senior level
Artificial Intelligence • Machine Learning • Database
The Role
The Data Scientist will develop and implement machine learning and AI models, focusing on improving model performance and building LLM-based products. Responsibilities include analyzing complex datasets, developing cloud-native solutions using GCP, and ensuring quality assurance of the machine learning models.
Summary Generated by Built In

Company Overview:

Blue Orange Digital is a cloud-based data transformation and predictive analytics development firm with offices in NYC and Washington, DC. From startups to Fortune 500s, we help companies make sense of their business challenges by applying modern data analytics techniques, visualizations, and AI/ML. Founded by engineers, we love passionate technologists and data analysts. Our startup DNA means everyone on the team makes a direct contribution to the growth of the company.

Position Overview: 

Blue Orange seeks an experienced Data Scientist with machine learning experience to expand our dynamic multi-disciplinary team. The ideal candidate will have strong experience with GCP including Vertex AI, Tensor, computer vision, and VR, and possess a deep passion for data science, machine learning, AI technologies, and innovative data solutions.

Note: This position requires candidates to be able to attend in-person work sessions at the New York City office at least one week per month, with occasional additional time required for collaboration. We’re looking for someone able to easily commute to the office to ensure smooth, in-person teamwork.

With proficiency in advanced machine learning and data techniques, strong skills in programming languages such as Python, deep expertise around data analytics and feature engineering, solid experience working with some of the main ML and data frameworks (Sklearn, XGBoost, LightGBM, TensorFlow, and/or PyTorch) experience working cloud technologies, GCP in particular, a proven track record of building cloud-native solutions in GCP using MLOps and LLMs. With strong proficiency in the whole end-to-end ML/AI cycle, from ideation to production. The candidate will play a crucial role in driving our machine-learning initiatives forward.

The candidate will have excellent communication skills to collaborate with technical and non-technical stakeholders effectively.

At Blue Orange, you'll have the opportunity to work on cutting-edge projects, leveraging modern machine-learning and AI techniques to deliver tangible business outcomes and drive innovation in our data-driven solutions.

Responsibilities: 

  • Develop and Implement Machine Learning and AI Models:
    • Design, build, and deploy advanced machine-learning models and applications
    • Improve model performance by conducting feature engineering, hyperparameter search, and metric selection
    • Build LLM-based products and stay up to date with current developments
    • Design and build custom APIs with tools like FastAPI
    • Build LLM orchestration systems with tools like LangChain in GCP
    • Build predictive analytics and modeling products using tools like Sklearn, Sktime, XGboosts, and/or LightGBM
  • Data Analytics and Processing:
    • Analyze large, complex datasets to extract actionable insights and inform model development
    • Implement data preprocessing, cleansing, and quality checks to ensure data quality
  • GCP Native Solutions and MLOps:
    • Develop and maintain cloud-native machine learning solutions using GCP (GKE, Anthos, Cloud Run, Gemini, Vertex AI, Tensor)
    • Implement and manage MLOps practices to automate and streamline the ML model deployment process. Using tools such as MLflow and/or Weights and Biases for storing metrics, artifacts, and experiments
  • Quality Assurance and Best Practices:
    • Ensure the highest quality of machine learning models through rigorous testing and validation. Using unit and integration testing with CI/CD pipelines and git-based source control
    • Advocate and adhere to best software practices (i.e., SOLID, DRY, Git version control, etc.) and machine learning (train, val, test data splits, baseline definition, overfitting management, etc) within the team

Requirements: 

  • 3-7 years of experience practicing Data Science and ML/AI data engineering
  • Degree in Computer Science, Engineering, Mathematics, or a related field
  • Strong mathematical skills, particularly in statistics and linear algebra
  • Experience with NLP and LLM-based technologies and frameworks
  • Deep Learning Expertise
  • Proficiency with Python, PyTorch (or tensorflow), notebooks, and AI applications
  • Experience with cloud-based technologies, particularly GCP
  • Expertise in training and deploying ML/AI-powered solutions in cloud environments
  • Ability to occasionally commute to Manhattan or the ability to be onsite at Manhattan client location for periodic week-long ideation, adoption, and launch sessions
  • A tenacious, curious mind driven to create impactive cutting edge solutions

Preferred qualifications:

  • Advanced degree in a relevant field
  • Publications in relevant AI/ML communities and journals
  • Optional: Experience working with classical NLP: Intent recognition, Named Entity Recognition (NER), and Part of Speech Tagging (POS), sklearn, spacy, Hugging Face, transformers, diffusion, etc. 
  • Experience with Hugging Face, Gemini, OpenAI, Anthropic, Cohere, LLamaIndex, Semantic Kernel, HayStack and/or related
  • Experience Fine-tuning OpenSource LLMs and deploying them.
  • Great Expectations, pytest, Looker, Databricks, and/or DBT a plus

Salary: $144,000 - $155,400 per year ($12,000 - $12,950 per month) - USD

Blue Orange Digital is an equal opportunity employer.

Background checks may be required for certain positions/projects.

Top Skills

Python
The Company
HQ: New York, NY
75 Employees
On-site Workplace
Year Founded: 2015

What We Do

Blue Orange is a data science and machine learning consulting and development firm. We build modern data warehousing to support machine learning and AI. We help companies integrate these insights to drive data-driven decision making.

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