Senior Data Scientist – VC Backed Startups

Jobtailor; New York (NY); On-site; USD 130,000 - 180,000; Full time

Job summary

Jobtailor in New York, NY is seeking an experienced Data Scientist to partner with product, engineering, and business leaders to identify high-impact opportunities and design experiments for product changes and growth initiatives. You will develop predictive and optimization models, apply causal inference, and build dashboards to track performance.

Collaboration with engineers will productionize models for customer-facing products, while mentoring junior data scientists and shaping the data

Qualifications

• 5+ years of experience in data science, applied statistics, machine learning, decision science, or a related field.
• Strong proficiency in Python, R, SQL, or similar analytical languages.
• Experience with statistical modeling, experimentation, causal inference, forecasting, or predictive analytics.
• Track record of using data to influence product strategy, customer outcomes, or business performance.
• Ability to work with large, complex, and imperfect datasets.
• Experience partnering with product managers, engineers, operators, and executive stakeholders.
• Strong communication skills and ability to explain technical findings clearly.
• Experience developing models or analytical systems used in production or operational decision-making.
• Strong judgment around methodology, measurement, tradeoffs, and uncertainty.
• Experience in venture-backed startups or rapidly scaling technology companies may be preferred.
• Advanced degree in statistics, economics, computer science, mathematics, operations research, or a related field may be preferred, but is not always required.
• Familiarity with technologies such as pandas, NumPy, SciPy, scikit-learn, XGBoost, LightGBM, PyTorch, TensorFlow, Snowflake, BigQuery, Redshift, Databricks, Spark, Looker, Tableau, Mode, Hex, Amplitude, Jupyter, dbt, Airflow, Git, Docker, and cloud platforms

Responsibilities

• Partner with product, engineering, and business leaders to identify high-impact data science opportunities
• Design and analyze experiments for product changes, growth initiatives, and operational strategies
• Develop predictive, forecasting, recommendation, ranking, and optimization models
• Apply statistical methods and causal inference techniques to measure impact and inform decisions
• Build metrics, analytical frameworks, and dashboards to improve visibility into product and business performance
• Translate complex analyses into clear recommendations for technical and non-technical stakeholders
• Collaborate with engineers to productionize models and integrate data science into customer-facing products
• Identify patterns in user, customer, operational, and market data
• Establish best practices for experimentation, model evaluation, data quality, and analytical rigor
• Mentor other data scientists and raise the technical standard of the broader data organization
• Help shape the company’s data strategy, tooling, and long-term analytical roadmap

Skills

Python

R

SQL

Statistical modeling

Experimentation

Causal inference

Forecasting

Production models

Communication

Cross-functional collaboration

Education

Advanced degree in statistics, economics, computer science, mathematics, operations research, or related field

Tools

pandas

NumPy

SciPy

scikit-learn

XGBoost

LightGBM

PyTorch

TensorFlow

Snowflake

BigQuery

Redshift

Databricks

Spark

Looker

Tableau

dbt

Airflow

Git

Docker

Job description

• Partner with product, engineering, and business leaders to identify high-impact data science opportunities
• Design and analyze experiments for product changes, growth initiatives, and operational strategies
• Develop predictive, forecasting, recommendation, ranking, and optimization models
• Apply statistical methods and causal inference techniques to measure impact and inform decisions
• Build metrics, analytical frameworks, and dashboards to improve visibility into product and business performance
• Translate complex analyses into clear recommendations for technical and non-technical stakeholders
• Collaborate with engineers to productionize models and integrate data science into customer-facing products
• Identify patterns in user, customer, operational, and market data
• Establish best practices for experimentation, model evaluation, data quality, and analytical rigor
• Mentor other data scientists and raise the technical standard of the broader data organization
• Help shape the company’s data strategy, tooling, and long-term analytical roadmap

Requirements

• 5+ years of experience in data science, applied statistics, machine learning, decision science, or a related field
• Strong proficiency in Python, R, SQL, or similar analytical languages
• Experience with statistical modeling, experimentation, causal inference, forecasting, or predictive analytics
• Track record of using data to influence product strategy, customer outcomes, or business performance
• Ability to work with large, complex, and imperfect datasets
• Experience partnering with product managers, engineers, operators, and executive stakeholders
• Strong communication skills and ability to explain technical findings clearly
• Experience developing models or analytical systems used in production or operational decision-making
• Strong judgment around methodology, measurement, tradeoffs, and uncertainty
• Experience in venture-backed startups or rapidly scaling technology companies may be preferred
• Advanced degree in statistics, economics, computer science, mathematics, operations research, or a related field may be preferred, but is not always required
• Familiarity with technologies such as pandas, NumPy, SciPy, scikit-learn, XGBoost, LightGBM, PyTorch, TensorFlow, Snowflake, BigQuery, Redshift, Databricks, Spark, Looker, Tableau, Mode, Hex, Amplitude, Jupyter, dbt, Airflow, Git, Docker, and cloud platforms

Core Competencies

Demonstrates expertise in data science, statistical modeling, and machine learning, with a strong ability to translate complex analyses into actionable insights for diverse stakeholders. Proficient in developing predictive models and analytical frameworks to drive product and business performance.