Senior Data Scientist- Azure & ML Specialist || Onsite- Pleasanton, CA (Relocation; Ok)

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Please find the job description given below and let me know your interest.

Position: Senior Data Scientist (Onsite)
Location: Pleasanton, CA (Relocation; Ok)
Duration: 6+ Months

Job Description

We seek a hands-on Senior Data Scientist to build, deploy, and optimize ML models at scale. Focus on Python/SQL-driven data pipelines, ML/DL modeling, visualization, and cloud-based production deployment. Strong emphasis on Azure ecosystem for enterprise data workflows.

Required Skills (Must-Have)

• Programming: Strong hands-on Python for data prep, modeling, ML components; SQL (joins, window functions, CTEs, query optimization).

• Machine Learning: Linear/Logistic Regression, Decision Trees, Random Forest, XGBoost/LightGBM, SVM, KNN; model evaluation (Precision/Recall, F1, ROC-AUC, MSE, RMSE); tuning (Grid/Randomized search, cross-validation).

• Deep Learning: TensorFlow/Keras/PyTorch; CNNs, RNNs/LSTMs, Transformers; use cases in NLP, computer vision, time-series.

• Data Wrangling: Missing data handling, feature engineering, cleaning, outlier detection, normalization/standardization.

• Data Visualization: Python (Matplotlib, Seaborn, Plotly); Tableau/Power BI for dashboards, reporting, storytelling.

• Databases: Relational (MySQL, PostgreSQL, SQL Server); NoSQL (MongoDB, Cassandra).

Desirable Skills (Preferred for Production/Advanced Roles)

• Big Data: Spark, Hadoop.

• Cloud (any one strongly preferred): Azure (Data Factory, Databricks, ML Studio, Synapse Analytics), AWS (S3, EC2, SageMaker), Google Cloud Platform (BigQuery, Vertex AI).

• PySpark on Databricks.

• Deployment: Flask/FastAPI, Docker/Kubernetes (optional), CI/CD basics.

• Data Pipelines: Airflow, Prefect (optional).

Apply if you have 10+ years delivering end-to-end ML solutions

Please share your updated resume and suggest the best number & time to connect with you