

NextGenPros Inc
Data Scientist
β - Featured Role | Apply direct with Data Freelance Hub
This role is for a Data Scientist in San Francisco, CA (Hybrid) on a contract basis, requiring 13-14+ years of experience. Key skills include Python, SQL, time-series modeling, ML pipelines, and cloud platforms.
π - Country
United States
π± - Currency
$ USD
-
π° - Day rate
Unknown
-
ποΈ - Date
March 20, 2026
π - Duration
Unknown
-
ποΈ - Location
Hybrid
-
π - Contract
Unknown
-
π - Security
Unknown
-
π - Location detailed
San Francisco Bay Area
-
π§ - Skills detailed
#Pandas #Statistics #Visualization #Anomaly Detection #Snowflake #BigQuery #A/B Testing #AWS (Amazon Web Services) #PySpark #Spark (Apache Spark) #Batch #NumPy #Cloud #ML (Machine Learning) #SQL (Structured Query Language) #Azure #Data Science #Data Engineering #Redshift #GCP (Google Cloud Platform) #Python #CRM (Customer Relationship Management) #Monitoring #Airflow
Role description
Position : Data Scientist
Location : San Francisco , CA-Hybrid
Type of Hire : Contract
Need 13-14 + years of Experience candidates
Key Responsibilities
β’ Design and productionize models for opportunity scanning, anomaly detection, and significant change detection across CRM, streaming, ecommerce, and social data.
β’ Define and tune alerting logic (thresholds, SLOs, precision/recall) to minimize noise while surfacing high-value marketing actions.
β’ Partner with marketing, product, and data engineering to operationalize insights into campaigns, playbooks, and automated workflows, with clear monitoring and experimentation.
Required Qualifications
β’ Strong proficiency in Python (pandas, NumPy, scikit-learn; plus experience with PySpark or similar for large-scale data) and SQL on modern warehouses (e.g., BigQuery, Snowflake, Redshift).
β’ Hands-on experience with time-series modeling and anomaly / changepoint / significant-movement detection(e.g., STL decomposition, EWMA/CUSUM, Bayesian/prophet-style models, isolation forests, robust statistics).
β’ Experience building and deploying production ML pipelines (batch and/or streaming), including feature engineering, model training, CI/CD, and monitoring for performance and data drift.
β’ Solid background in statistics and experimentation: hypothesis testing, power analysis, A/B testing frameworks, uplift/propensity modeling, and basic causal inference techniques.
β’ Familiarity with cloud platforms (GCP/AWS/Azure), orchestration tools (e.g., Airflow/Prefect), and dashboarding/visualization tools to expose alerts and model outputs to business users.
Position : Data Scientist
Location : San Francisco , CA-Hybrid
Type of Hire : Contract
Need 13-14 + years of Experience candidates
Key Responsibilities
β’ Design and productionize models for opportunity scanning, anomaly detection, and significant change detection across CRM, streaming, ecommerce, and social data.
β’ Define and tune alerting logic (thresholds, SLOs, precision/recall) to minimize noise while surfacing high-value marketing actions.
β’ Partner with marketing, product, and data engineering to operationalize insights into campaigns, playbooks, and automated workflows, with clear monitoring and experimentation.
Required Qualifications
β’ Strong proficiency in Python (pandas, NumPy, scikit-learn; plus experience with PySpark or similar for large-scale data) and SQL on modern warehouses (e.g., BigQuery, Snowflake, Redshift).
β’ Hands-on experience with time-series modeling and anomaly / changepoint / significant-movement detection(e.g., STL decomposition, EWMA/CUSUM, Bayesian/prophet-style models, isolation forests, robust statistics).
β’ Experience building and deploying production ML pipelines (batch and/or streaming), including feature engineering, model training, CI/CD, and monitoring for performance and data drift.
β’ Solid background in statistics and experimentation: hypothesis testing, power analysis, A/B testing frameworks, uplift/propensity modeling, and basic causal inference techniques.
β’ Familiarity with cloud platforms (GCP/AWS/Azure), orchestration tools (e.g., Airflow/Prefect), and dashboarding/visualization tools to expose alerts and model outputs to business users.






