Helloconstellation
Overview
Constellation is a cutting-edge AI solution that empowers highly regulated and complex industries with insights and content to fuel business. We specialize in healthcare, automotive, insurance, and finance, enabling customers to harness data and streamline the creation of localized, personalized content. A global, NYC-based company, Constellation has been revolutionizing marketing technology and data intelligence since 2016. Constellation was named among fastest-growing companies by Inc. 500, reflecting our rapid growth and impact. In 2022, our platform won the Digiday Technology Award for Best Marketing Automation Platform. About the Role
We are seeking an experienced Senior Data Scientist to spearhead the development and optimization of our automotive predictive models. This role involves leading end-to-end model developmentfrom data preprocessing to deploymentand collaborating with cross-functional teams to deliver scalable, high-impact AI models and solutions. The ideal candidate is a strategic thinker with deep expertise in machine learning, deep learning, and transformer architectures, self-motivated, and capable of driving and advancing projects. What Youll Do
Model Development: Architect, develop, and fine-tune inventory predictive models to address complex decision-making challenges. Model Evaluation: Define and implement metrics to evaluate model performance, iterating on designs to improve accuracy, efficiency, and robustness. Model Deployment: Collaborate with engineering teams to deploy models into production environments, ensuring scalability, reliability, and performance. Documentation: Document methodologies, experiments, and results. Research and Innovation: Stay at the forefront of advancements in deep learning, transformer architectures, reinforcement learning, and sequential decision-making, applying cutting-edge techniques to enhance model performance. Mentor & Scale the Team: Coach junior and mid-level data scientists and engineers, review code, drive standards, and help shape a culture of high performance, curiosity, and inclusivity. Collaborate Cross-Functionally: Work with Product, Engineering, Design, and GTM teams to integrate intelligent systems into customer-facing features and internal tooling. Model Business-Critical Outcomes: Develop models for inventory and pricing optimizations, leveraging both structured and unstructured data. What Were Looking For
Experience: 8+ years in data science, ML engineering, or applied AI, with a track record of delivering high-performance models and shipping models in production. Familiarity with automotive data domains is a strong plus, whether in marketing analytics or vehicle inventory intelligence. Technical Expertise: Deep experience with Python and classic ML (Pandas, NumPy, Scikit-learn) and modern ML/DL libraries (PyTorch, TensorFlow, Hugging Face). Experience leveraging longitudinal data to uncover trends and predictive insights for complex, dynamic datasets. Preprocessing: Prepare structured and unstructured data for ML/DL models, ensuring data quality and feature engineering. Deep understanding of transformer architectures, reinforcement learning, and sequential decision-making models. SQL and cloud data warehouses (e.g., Snowflake, BigQuery, Redshift). Agile experience: Participated in sprints and iterative project cycles to deliver data-driven solutions. Production-grade code: Develop and maintain scalable data pipelines and ML/DL models. Problem Solving: Strong analytical skills with a track record of solving complex, real-world problems using data-driven approaches. Ownership and leadership: Lead projects, mentor team members, and manage end-to-end model development lifecycles. Communication: Collaborative mindset and passion for helping others grow. Bonus Experience
Model lifecycle management, pipelines, monitoring, and experiment tracking (e.g., MLflow, SageMaker, Vertex AI). Experience building systems on AWS (Lambda, SageMaker, EC2, Batch, S3) or similar cloud platforms. Probabilistic modeling (e.g., PyMC3, Stan). Graph databases (e.g., Neo4j) and modeling network effects. Experience with recommendation engines, survival models, or multi-touch attribution. Exposure to Looker, Tableau, or similar BI platforms. Diversity & Inclusion
Constellation is an Equal Opportunity Employer and commits to a diverse and inclusive environment. We do not discriminate on race, color, religion, national origin, sex, gender, age, disability, veteran status, genetic information, sexual orientation, gender identity, or other protected bases under federal, state, or local law. If you need an accommodation during any part of the interview process, please contact your Talent Partner. Compensation Package
The total compensation package includes base salary, equity, and benefits. New York Pay Range: $165,000 - $185,000 #J-18808-Ljbffr
Constellation is a cutting-edge AI solution that empowers highly regulated and complex industries with insights and content to fuel business. We specialize in healthcare, automotive, insurance, and finance, enabling customers to harness data and streamline the creation of localized, personalized content. A global, NYC-based company, Constellation has been revolutionizing marketing technology and data intelligence since 2016. Constellation was named among fastest-growing companies by Inc. 500, reflecting our rapid growth and impact. In 2022, our platform won the Digiday Technology Award for Best Marketing Automation Platform. About the Role
We are seeking an experienced Senior Data Scientist to spearhead the development and optimization of our automotive predictive models. This role involves leading end-to-end model developmentfrom data preprocessing to deploymentand collaborating with cross-functional teams to deliver scalable, high-impact AI models and solutions. The ideal candidate is a strategic thinker with deep expertise in machine learning, deep learning, and transformer architectures, self-motivated, and capable of driving and advancing projects. What Youll Do
Model Development: Architect, develop, and fine-tune inventory predictive models to address complex decision-making challenges. Model Evaluation: Define and implement metrics to evaluate model performance, iterating on designs to improve accuracy, efficiency, and robustness. Model Deployment: Collaborate with engineering teams to deploy models into production environments, ensuring scalability, reliability, and performance. Documentation: Document methodologies, experiments, and results. Research and Innovation: Stay at the forefront of advancements in deep learning, transformer architectures, reinforcement learning, and sequential decision-making, applying cutting-edge techniques to enhance model performance. Mentor & Scale the Team: Coach junior and mid-level data scientists and engineers, review code, drive standards, and help shape a culture of high performance, curiosity, and inclusivity. Collaborate Cross-Functionally: Work with Product, Engineering, Design, and GTM teams to integrate intelligent systems into customer-facing features and internal tooling. Model Business-Critical Outcomes: Develop models for inventory and pricing optimizations, leveraging both structured and unstructured data. What Were Looking For
Experience: 8+ years in data science, ML engineering, or applied AI, with a track record of delivering high-performance models and shipping models in production. Familiarity with automotive data domains is a strong plus, whether in marketing analytics or vehicle inventory intelligence. Technical Expertise: Deep experience with Python and classic ML (Pandas, NumPy, Scikit-learn) and modern ML/DL libraries (PyTorch, TensorFlow, Hugging Face). Experience leveraging longitudinal data to uncover trends and predictive insights for complex, dynamic datasets. Preprocessing: Prepare structured and unstructured data for ML/DL models, ensuring data quality and feature engineering. Deep understanding of transformer architectures, reinforcement learning, and sequential decision-making models. SQL and cloud data warehouses (e.g., Snowflake, BigQuery, Redshift). Agile experience: Participated in sprints and iterative project cycles to deliver data-driven solutions. Production-grade code: Develop and maintain scalable data pipelines and ML/DL models. Problem Solving: Strong analytical skills with a track record of solving complex, real-world problems using data-driven approaches. Ownership and leadership: Lead projects, mentor team members, and manage end-to-end model development lifecycles. Communication: Collaborative mindset and passion for helping others grow. Bonus Experience
Model lifecycle management, pipelines, monitoring, and experiment tracking (e.g., MLflow, SageMaker, Vertex AI). Experience building systems on AWS (Lambda, SageMaker, EC2, Batch, S3) or similar cloud platforms. Probabilistic modeling (e.g., PyMC3, Stan). Graph databases (e.g., Neo4j) and modeling network effects. Experience with recommendation engines, survival models, or multi-touch attribution. Exposure to Looker, Tableau, or similar BI platforms. Diversity & Inclusion
Constellation is an Equal Opportunity Employer and commits to a diverse and inclusive environment. We do not discriminate on race, color, religion, national origin, sex, gender, age, disability, veteran status, genetic information, sexual orientation, gender identity, or other protected bases under federal, state, or local law. If you need an accommodation during any part of the interview process, please contact your Talent Partner. Compensation Package
The total compensation package includes base salary, equity, and benefits. New York Pay Range: $165,000 - $185,000 #J-18808-Ljbffr