SGS Consulting
Senior Product Data Scientist
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is a Senior Product Data Scientist on a W2 contract for over 6 months, paying $75–$100/hour. Key skills include SQL, Python, and product strategy. Experience in building 0-1 products is essential; ML-focused candidates are not suitable.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
800
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🗓️ - Date
July 1, 2026
🕒 - Duration
More than 6 months
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🏝️ - Location
Unknown
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📄 - Contract
W2 Contractor
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🔒 - Security
Unknown
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📍 - Location detailed
United States
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🧠 - Skills detailed
#Datasets #Forecasting #Python #Statistics #Data Quality #SQL (Structured Query Language) #Automation #Strategy #Data Analysis #Data Wrangling #ML (Machine Learning) #Data Engineering #Monitoring #Documentation #A/B Testing #Data Pipeline #Regression #Data Science #"ETL (Extract #Transform #Load)"
Role description
About the Role:
• W2 contract role with the possibility of extension.
• Pay range: $75–$100/hour on W2, negotiable based on experience.
• Candidates whose primary experience is in ML ranking/algorithms are not a fit for this role.
What we are looking for:
• Seeking a temporary Data Scientist to support analytics and data-driven decision-making across cross-functional stakeholders. In this role, you will analyze large datasets, develop insights and measurement approaches for new product innovation and iterations, and communicate findings to inform strategy and execution. This is a temporary role and is not a full-time position with Client.
Responsibilities:
• Analyze large, complex datasets to identify trends, opportunities, and key drivers of business outcomes.
• Design and evaluate experiments (e.g., A/B tests), measurement frameworks, and KPI definitions.
• Build and maintain reproducible analyses, dashboards, and reporting to enable ongoing monitoring.
• Develop statistical and operational research models to support planning, forecasting, optimization, and prioritization.
• Partner with stakeholders to translate business questions into analytical approaches, and present results in clear, actionable narratives.
• Ensure data quality through validation, documentation, and clear assumptions in analysis.
Minimum Requirements:
• Experience applying SQL to extract, transform, and analyze large-scale data.
• Proficiency in Python for data analysis (e.g., data wrangling, statistical analysis, modeling, automation).
• Strong foundation in statistics (e.g., hypothesis testing, regression, inference, experimental design).
• Knowledge of operational research techniques (e.g., optimization, simulation, decision analysis) and ability to apply them to real business problems.
• Demonstrated ability to communicate technical findings to non-technical audiences and influence decision making.
• Ability to manage multiple priorities in a fast-paced environment and deliver high-quality work within defined timelines.
Must-Have Skills:
• Proven experience using DS skills to build 0 - 1 products.
• Python + SQL experience.
• Product strategy (new product experience).
Nice-to-have Skills:
• Data pipeline/Data Engineer background.
• Big Tech experience.
Interviews:
• How many rounds of interviews: 1 - 2.
• Types of Interviews: Behavioral + technical rounds.
• Interview Duration: 45 mins.
About the Role:
• W2 contract role with the possibility of extension.
• Pay range: $75–$100/hour on W2, negotiable based on experience.
• Candidates whose primary experience is in ML ranking/algorithms are not a fit for this role.
What we are looking for:
• Seeking a temporary Data Scientist to support analytics and data-driven decision-making across cross-functional stakeholders. In this role, you will analyze large datasets, develop insights and measurement approaches for new product innovation and iterations, and communicate findings to inform strategy and execution. This is a temporary role and is not a full-time position with Client.
Responsibilities:
• Analyze large, complex datasets to identify trends, opportunities, and key drivers of business outcomes.
• Design and evaluate experiments (e.g., A/B tests), measurement frameworks, and KPI definitions.
• Build and maintain reproducible analyses, dashboards, and reporting to enable ongoing monitoring.
• Develop statistical and operational research models to support planning, forecasting, optimization, and prioritization.
• Partner with stakeholders to translate business questions into analytical approaches, and present results in clear, actionable narratives.
• Ensure data quality through validation, documentation, and clear assumptions in analysis.
Minimum Requirements:
• Experience applying SQL to extract, transform, and analyze large-scale data.
• Proficiency in Python for data analysis (e.g., data wrangling, statistical analysis, modeling, automation).
• Strong foundation in statistics (e.g., hypothesis testing, regression, inference, experimental design).
• Knowledge of operational research techniques (e.g., optimization, simulation, decision analysis) and ability to apply them to real business problems.
• Demonstrated ability to communicate technical findings to non-technical audiences and influence decision making.
• Ability to manage multiple priorities in a fast-paced environment and deliver high-quality work within defined timelines.
Must-Have Skills:
• Proven experience using DS skills to build 0 - 1 products.
• Python + SQL experience.
• Product strategy (new product experience).
Nice-to-have Skills:
• Data pipeline/Data Engineer background.
• Big Tech experience.
Interviews:
• How many rounds of interviews: 1 - 2.
• Types of Interviews: Behavioral + technical rounds.
• Interview Duration: 45 mins.
