Blue Orange Digital
Data Scientist
Blue Orange Digital, New York, New York, us, 10261
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.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), and experience working with cloud technologies, GCP in particular, a proven track record of building cloud-native solutions in GCP using MLOps and LLMs. 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 applicationsImprove model performance by conducting feature engineering, hyperparameter search, and metric selectionBuild LLM-based products and stay up to date with current developmentsDesign and build custom APIs with tools like FastAPIBuild LLM orchestration systems with tools like LangChain in GCPBuild 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 developmentImplement 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 controlAdvocate 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 engineeringDegree in Computer Science, Engineering, Mathematics, or a related fieldStrong mathematical skills, particularly in statistics and linear algebraExperience with NLP and LLM-based technologies and frameworksDeep Learning ExpertiseProficiency with Python, PyTorch (or TensorFlow), notebooks, and AI applicationsExperience with cloud-based technologies, particularly GCPExpertise in training and deploying ML/AI-powered solutions in cloud environmentsAbility to occasionally commute to Manhattan or the ability to be onsite at Manhattan client location for periodic week-long ideation, adoption, and launch sessionsA tenacious, curious mind driven to create impactive cutting-edge solutionsPreferred qualifications:Advanced degree in a relevant fieldPublications in relevant AI/ML communities and journalsOptional: 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 relatedExperience Fine-tuning OpenSource LLMs and deploying them.Great Expectations, pytest, Looker, Databricks, and/or DBT a plusSalary:
$144,000 - $155,400 per year ($12,000 - $12,950 per month) - USDBlue Orange Digital is an equal opportunity employer.Background checks may be required for certain positions/projects.
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Design, build, and deploy advanced machine-learning models and applicationsImprove model performance by conducting feature engineering, hyperparameter search, and metric selectionBuild LLM-based products and stay up to date with current developmentsDesign and build custom APIs with tools like FastAPIBuild LLM orchestration systems with tools like LangChain in GCPBuild 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 developmentImplement 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 controlAdvocate 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 engineeringDegree in Computer Science, Engineering, Mathematics, or a related fieldStrong mathematical skills, particularly in statistics and linear algebraExperience with NLP and LLM-based technologies and frameworksDeep Learning ExpertiseProficiency with Python, PyTorch (or TensorFlow), notebooks, and AI applicationsExperience with cloud-based technologies, particularly GCPExpertise in training and deploying ML/AI-powered solutions in cloud environmentsAbility to occasionally commute to Manhattan or the ability to be onsite at Manhattan client location for periodic week-long ideation, adoption, and launch sessionsA tenacious, curious mind driven to create impactive cutting-edge solutionsPreferred qualifications:Advanced degree in a relevant fieldPublications in relevant AI/ML communities and journalsOptional: 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 relatedExperience Fine-tuning OpenSource LLMs and deploying them.Great Expectations, pytest, Looker, Databricks, and/or DBT a plusSalary:
$144,000 - $155,400 per year ($12,000 - $12,950 per month) - USDBlue Orange Digital is an equal opportunity employer.Background checks may be required for certain positions/projects.
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