Senior Product Data Scientist

Posted about 2 months agoViewed

💎 Seniority level: Senior, 4-6 years of industry experience

📍 Location: US

💸 Salary: 140000.0 - 170000.0 USD per year

🔍 Industry: Health and fitness

🗣️ Languages: English

⏳ Experience: 4-6 years of industry experience

🪄 Skills: PythonSQLData AnalysisMachine LearningSnowflakeAmplitude AnalyticsTableauData visualization

MS in Computer Science, Data Science, or similar quantitative field OR 2+ years of relevant experience.
4-6 years of industry experience with machine learning and 3 years in digital consumer products.
Experience with supervised and unsupervised learning algorithms, including decision trees and clustering.
Proficiency in SQL, Python, R, or other data analysis languages.
In-depth knowledge of Statistics, Probability, and Machine Learning.
Ability to communicate specialized data insights clearly.

Perform large-scale hypothesis testing and statistical analysis to derive insights.
Conduct analyses for customer segmentation, new business opportunities, and predictive modeling.
Optimize dynamic pricing and model predictive churn & retention.
Collaborate with product leadership to identify growth trends.
Support product managers in enhancing product offerings.

Posted 7 days ago

📍 USA

🧭 Full-Time

💸 145000.0 - 175000.0 USD per year

🔍 FinTech and PropTech

🔧 Requirements

BA in Statistics, Mathematics, Computer Science, or a related quantitative field.
3+ years of experience in data science, including experience in product analytics or similar domains.
Expertise in SQL, Python, and statistical tools/libraries such as NumPy or Pandas.
Strong understanding of machine learning, statistical modeling techniques, and A/B testing.
Experience with business intelligence tools such as Tableau, Sigma, or Looker.
Proven ability to share outcomes through written and verbal communication, including the ability to effectively communicate with both business and technical teams.

💡 Responsibilities

Develop and optimize data models and pipelines to support customer-facing analytics and internal decision-making.
Build self-service tools, dashboards, and visualizations to empower end users and internal stakeholders with actionable insights.
Partner with data engineers to ensure models are secure, performant, and scalable.
Provide thought leadership on data science best practices, tools, and methodologies.
Communicate complex findings effectively to both technical and non-technical audiences through written and visual storytelling.

PythonSQLData AnalysisMachine LearningNumpyTableauPandasData modelingA/B testing

Posted 7 days ago