This is a full time, hybrid opportunity in NYC

In this role, you will be responsible for the entire data analysis lifecycle, from transforming raw data to creating insightful visualizations and reports. You will wrangle, cleanse, and transform large datasets to prepare them for AI consumption. You will also develop and implement data pipelines to automate data ingestion, processing, and delivery for AI models.

Integrate with data platforms and tools to ensure efficient and scalable data processing for AI initiatives. You will also play a key role in developing and maintaining the data infrastructure that supports our analytics efforts.

In this role, you should be highly analytical and passionate about analysis, math, and statistics. Critical thinking and problem-solving skills are essential for interpreting data. Experience with AI, machine learning, and research is a big plus. Your goal will help our company analyze trends to make better decisions.

Your Responsibilities:

• Design, develop, and implement data pipelines to collect, clean, and transform data from various sources
• Identify valuable data sources and automate collection processes
• Undertake preprocessing of structured and unstructured data
• Assist with data labeling and tagging
• Analyze large amounts of information to discover trends and patterns
• Present information using data visualization techniques
• Propose solutions and strategies to business challenges
• Collaborate with engineering and product development teams
• Perform feature engineering for AI applications

What Skills Are Required:

• BS/ MS /PhD in Computer Science, Engineering, or relevant field; graduate degree in Data Science or other quantitative field is preferred
• 5 years of experience as a Data Scientist or Data Analyst
• Experience in data mining
• Understanding of machine learning and operations research
• Knowledge of SQL and Python; Python ML frameworks familiarity is a plus; familiarity with Java is a big plus
• Experience using ELK Stack (Elasticsearch, Logstash, Kibana)
• Experience using business intelligence tools (e.g., Tableau) and data frameworks (e.g., Hadoop)
• Experience with AI/ML-based solutions for data analysis is a big plus
• Analytical mind and business acumen
• Strong math skills (e.g. statistics, algebra)