Data Scientist

Summary

8 years of experience as data scientist ,Embed with business stakeholders to identify, test, and implement short and long-term data roadmap and strategy solutions that drive business with customer success.
Own full cycle of machine learning and causal inference products from ideation and training through deployment into our production environment.
Produced high quality materials (PowerPoint, product metrics and KPIs etc.) giving demonstrations to both internally (sales, customer success, product engineering, etc.) and with customers on the performance of AI solutions as well as data science issues.
Experience in Preparing data from relational databases and soap services and Hadoop clusters for data mining and feature engineering within large datasets with complex classes and anomalies using python, SQL.
Experience creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks etc.
Lead and support analytical projects by providing Statistical expertise in study design, statistic modeling, data analysis, outcome interpretation and communication.
Highly methodical in approach and possess quick grasping abilities with keen interest to upgrade skills by acquiring knowledge.
Familiarity with modern data science libraries and tools, including but not limited to Gurobi, Pulp, Scipy, Scikit-learn, Pandas, TensorFlow, Keras, and similar.

Expectations

growth, great culture

Employment Preferences

Expected Base Salary

**0,000 USD

Expected Hourly Rate

** USD/hr

Academic Degree

Experience

Skills

• Python
• SQL
• T-SQL
• R
• Spark
• Alteryx
• Pandas
• Numpy
• Matplotlib
• Sci-kit Learn
• Tensor Flow
• Open CV
• Keras
• PyTorch
• Statistical Analysis
• Time Series
• Machine Learning
• Linear Regression
• Logistic Regression
• Random Forests Algorithm
• Decisions Trees
• K- Means Cluster Analysis
• Deep Learnings
• ANN
• CNN
• RNN
• Natural Language Processing
• Clustering
• Regression
• Classification
• Principal Component Analysis
• Recommendation System.
• Amazon Web Services
• AWS
• Microsoft Azure
• Google Cloud
• Qliksense
• PowerBI
• Plotly
• Seaborn
• GgPlot
• Tableau
• Big Query
• Snowflake
• Amazon S3
• Teradata
• GitHub
• MLFlow
• DVC
• EvidentlyAI
• Meta Flow
• Seldon
• Apache Hadoop
• Apache Airflow
• Databricks
• Amazon Sage Maker
• Azure Data Factory
• Docker
• Kubernetes
• FastAPI
• MongoDB