~6mo ago
$225k and $275k/yr

AI Data Scientist

United StatesUnited States·New Yorkmid
Data ScienceOtherData EngineeringData ScientistData EngineerAi Data EngineerDataData & AI
8 views0 saves0 applied

Quick Summary

Overview

About the Role Schonfeld Strategic Advisors is seeking an experienced AI Data Engineer to join our Data Engineering team. In this role, you will be responsible for designing, building, and maintaining robust data pipelines that power SchonAI, our firm's internal AI platform.

Key Responsibilities

Data Pipeline Development Design and build scalable, reliable data pipelines to ingest, transform, and deliver structured and unstructured data to SchonAI using Prefect.

Requirements Summary

Technical Skills Programming: Strong proficiency in Python; experience with SQL and at least one other language (e.g. Java, Scala, Go, Rust) Data Engineering: 5+ years of experience building production data pipelines using tools like Apache Airflow,…

Technical Tools
airflowawsdockerdynamodbelasticsearchgcpgojavakafkakubernetesmongodbmysqlpostgresqlpythonrustscalasqletl

About the Role

~1 min read

Schonfeld Strategic Advisors is seeking an AI Data Scientist to help build the data and analytics foundation powering our growing agentic AI capabilities for investment research. This is a hands-on role that sits at the intersection of AI, data science and data engineering: you will build the pipelines and datasets that feed our internal AI platform, dig into the data itself to analyze it and engineer features, and help shape how it is used for modeling and research. We're looking for someone equally comfortable designing robust data solutions and exploring data to uncover insights, and who is passionate about applying these skills to complex data problems alongside our investment teams.

Responsibilities

~1 min read
  • Design and build scalable, reliable data pipelines to ingest, transform, and deliver structured and unstructured data.
  • Implement real-time and batch data processing workflows to meet varying latency requirements.
  • Ensure data quality, consistency, and integrity across all pipelines.
  • Explore, clean, and analyze new and existing datasets to build a deep understanding of their structure, quality, and potential applications.
  • Engineer features and curate research-ready datasets for training, fine-tuning, and model evaluation.
  • Conduct exploratory analysis to assess data coverage, surface insights, and validate suitability for research and AI use cases.
  • Build and maintain data infrastructure for AI/ML workloads, including vector databases and semantic search systems.
  • Design data schemas and storage solutions that support efficient retrieval and processing for LLM applications.
  • Contribute to data versioning, lineage tracking, and observability for AI training and inference pipelines.
  • Partner with cross-functional teams, including AI engineers, researchers, and business stakeholders, to understand data needs and design solutions.
  • Collaborate with infrastructure teams on cloud architecture, security, and compliance requirements.

 

Requirements

~1 min read

Technical Skills

  • Programming: Strong proficiency in Python and SQL (experience with an additional language such as Java, Scala, or Go is a plus)
  • Pipeline Development: Building and orchestrating production data pipelines and ETL/ELT workflows (e.g., Apache Airflow, Prefect, Dagster)
  • Data Modeling & Storage: Designing schemas and working with SQL and NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB, Elasticsearch)
  • Data Analysis & Modeling: Analyzing data and developing models using statistical and machine learning tools such as XGBoost, PyTorch, and TensorFlow; performing feature engineering, model training, and evaluation.
  • Cloud Platforms: Working with a major cloud provider (AWS, GCP, or Azure) and core storage and compute services
  • AI/ML Data: Preparing and serving data for ML/AI systems, including vector databases (e.g., Pinecone, Weaviate, Qdrant) and embedding pipelines

Preferred Experience

  • Financial domain knowledge — e.g., quantitative research or data science experience at a buy-side or sell-side firm
  • Experience supporting LLM applications or RAG (Retrieval Augmented Generation) systems
  • Familiarity with distributed computing frameworks (Spark, Flink) or large-scale data platforms
  • Familiarity with financial data sources (market data, fundamental data, alternative data)
  • Knowledge of data streaming technologies (Kafka, Kinesis, Pub/Sub)
  • Experience with data quality frameworks (Great Expectations, Deequ)
  • Bachelor's, Master's, or PhD in Computer Science, Data Science, or a related field
  • Strong problem-solving skills and attention to detail
  • Excellent communication skills with ability to translate technical concepts for non-technical stakeholders
  • Experience working in fast-paced, collaborative environments
  • Self-motivated with ability to manage multiple priorities

Who we are  
Schonfeld is a global multi-manager hedge fund that strives to deliver industry-leading risk-adjusted returns for our investors. We leverage both internal and external portfolio manager teams around the world, seeking to capitalize on inefficiencies and opportunities within the markets. We draw from decades of experience and a significant investment in proprietary technology, infrastructure and risk analytics to invest across four main strategies: Quant, Tactical, Fundamental Equity and Discretionary Macro & Fixed Income.

Our Culture
At Schonfeld, we’ll invest in you. Attracting and retaining top talent is at the heart of what we do, because we believe that exceptional outcomes begin with exceptional people. We foster a culture where talent is empowered to continually learn, innovate and pursue ambitious goals. We are teamwork-oriented, collaborative and encourage ideas—at all levels—to be shared. As an organization committed to investing in our people, we provide learning and educational offerings and opportunities to make an impact. We encourage community through internal networks, external partnerships and service initiatives that promote inclusion and purpose beyond the firm’s walls.

The base pay for this role is expected to be between $225k and $275k. The expected base pay range is based on information at the time this post was generated. This role may also be eligible for other forms of compensation such as a performance bonus and a competitive benefits package. Actual compensation for the successful candidate will be determined based on a variety of factors such as skills, qualifications, and experience.

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Location & Eligibility

Where is the job
New York, United States
On-site at the office
Who can apply
US
Listed under
United States

About this job

Pay per year
$225,000–$275,000 a year
32% above the $190,000 median for Data Scientist jobs on Jobera (780 salaries).
Who can apply
United States
Posted
209 days ago
Employer
has 71 open jobs on Jobera in 6 countries.

Listing Details

First seen
March 26, 2026
Last seen
October 21, 2026

Posting Health

Days active
209
Repost count
0
Trust Level
42%
Scored at
October 22, 2026

Signal breakdown

freshnesssource trustcontent trustemployer trust
Employees
501-1,000
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AI Data Scientist $225k and $275k