Ascii Group, LLC
Senior Data Scientist - W2 Only
⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Senior Data Scientist in Pleasanton, CA, for 12+ months at a W2 pay rate. Key skills include Python, SQL, Azure Data Factory, Spark/PySpark, and machine learning frameworks. Requires 9+ years of relevant experience.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
February 18, 2026
🕒 - Duration
More than 6 months
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🏝️ - Location
On-site
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📄 - Contract
W2 Contractor
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🔒 - Security
Unknown
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📍 - Location detailed
Pleasanton, CA
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🧠 - Skills detailed
#Data Cleaning #MongoDB #ML (Machine Learning) #Big Data #SQL (Structured Query Language) #SQL Server #Normalization #Deep Learning #AWS S3 (Amazon Simple Storage Service) #Model Evaluation #"ETL (Extract #Transform #Load)" #Transformers #Airflow #Regression #Data Wrangling #BI (Business Intelligence) #S3 (Amazon Simple Storage Service) #AWS (Amazon Web Services) #MySQL #Forecasting #NLP (Natural Language Processing) #Storytelling #Azure Data Factory #Cloud #Model Deployment #ADF (Azure Data Factory) #Flask #EC2 #Kubernetes #Matplotlib #Synapse #Tableau #Azure #Data Engineering #Data Science #Databricks #TensorFlow #Azure Synapse Analytics #Logistic Regression #PyTorch #Hadoop #FastAPI #Data Pipeline #NoSQL #Programming #Keras #PostgreSQL #Databases #PySpark #Docker #SageMaker #Plotly #Data Processing #GCP (Google Cloud Platform) #Spark (Apache Spark) #Visualization #AI (Artificial Intelligence) #Data Framework #Microsoft Power BI #Deployment #Python
Role description
The following requirement is open with our client.
Title : Senior Data Scientist (W2)
Location : Pleasanton, CA
Duration : 12+ Months
Relevant Experience (in Yrs.): 9+
Job Description:
1.Programming Languages
· Strong Python familiarity (hands-on) for data prep, modeling, and building ML components.
· SQL - Skills: joins, window functions, CTEs, query optimization
1. Machine Learning
· Linear/Logistic Regression
· Decision Trees, Random Forest, XGBoost, LightGBM
· SVM, KNN
· Model evaluation - Precision/Recall, F1, ROC-AUC, MSE, RMSE
· Model tuning - Grid search, randomized search, cross-validation
1. Deep Learning
· Frameworks: TensorFlow, Keras, PyTorch
· CNNs, RNNs, LSTMs, Transformers
· Use cases: NLP, computer vision, time-series forecasting
1. Data Wrangling & Preprocessing
· Missing data handling
· Feature engineering
· Data cleaning
· Outlier detection
Normalization standardization
1. Data Visualization BI Tools Python Matplotlib| Seaborn| Plotly Tools Tableau| Power BI Dashboards| reporting| storytelling with data
1. Big Data Cloud Tools (Needed for production-scale roles) Big Data Frameworks Spark| Hadoop Cloud Platforms (any one strongly) AWS (S3| EC2| SageMaker) Azure (Data Factory| Databricks| ML Studio) GCP (Big Query| Vertex AI)
1. Deployment Skills (advanced roles) Model deployment Flask| FastAPI Docker| Kubernetes (optional)CICD basics
1. Databases Data Engineering Basics Relational MySQL| PostgreSQL| SQL Server NoSQL MongoDB| Cassandra Data pipelines Airflow| Prefect (optional)
Desirable Skills: Azure data factory| Databricks| Azure Synapse Analytics Python| Sql |Pyspark Databricks
Must-Have Skills:
• Azure data factory
• Python
• SQL
• Spark / PySpark (Big Data Processing)
• Azure/AWS/GCP
The following requirement is open with our client.
Title : Senior Data Scientist (W2)
Location : Pleasanton, CA
Duration : 12+ Months
Relevant Experience (in Yrs.): 9+
Job Description:
1.Programming Languages
· Strong Python familiarity (hands-on) for data prep, modeling, and building ML components.
· SQL - Skills: joins, window functions, CTEs, query optimization
1. Machine Learning
· Linear/Logistic Regression
· Decision Trees, Random Forest, XGBoost, LightGBM
· SVM, KNN
· Model evaluation - Precision/Recall, F1, ROC-AUC, MSE, RMSE
· Model tuning - Grid search, randomized search, cross-validation
1. Deep Learning
· Frameworks: TensorFlow, Keras, PyTorch
· CNNs, RNNs, LSTMs, Transformers
· Use cases: NLP, computer vision, time-series forecasting
1. Data Wrangling & Preprocessing
· Missing data handling
· Feature engineering
· Data cleaning
· Outlier detection
Normalization standardization
1. Data Visualization BI Tools Python Matplotlib| Seaborn| Plotly Tools Tableau| Power BI Dashboards| reporting| storytelling with data
1. Big Data Cloud Tools (Needed for production-scale roles) Big Data Frameworks Spark| Hadoop Cloud Platforms (any one strongly) AWS (S3| EC2| SageMaker) Azure (Data Factory| Databricks| ML Studio) GCP (Big Query| Vertex AI)
1. Deployment Skills (advanced roles) Model deployment Flask| FastAPI Docker| Kubernetes (optional)CICD basics
1. Databases Data Engineering Basics Relational MySQL| PostgreSQL| SQL Server NoSQL MongoDB| Cassandra Data pipelines Airflow| Prefect (optional)
Desirable Skills: Azure data factory| Databricks| Azure Synapse Analytics Python| Sql |Pyspark Databricks
Must-Have Skills:
• Azure data factory
• Python
• SQL
• Spark / PySpark (Big Data Processing)
• Azure/AWS/GCP
