Data Scientist - Machine Learning Focus

Adidev Technologies
San Jose, United States of America
yesterday

Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Intermediate

Job location

San Jose, United States of America

Tech stack

Amazon Web Services (AWS)
Data analysis
Artificial Neural Networks
Computer Vision
Cloud Computing
Cluster Analysis
ETL
Distributed Systems
Genetic Algorithm
Python
PostgreSQL
Linear Programming
Machine Learning
MongoDB
Natural Language Processing
NumPy
Principal Component Analysis
TensorFlow
SQL Databases
Data Processing
PyTorch
Flask
Random Forest
Deep Learning
Keras
Pandas
Scikit Learn
Kubernetes
XGBoost
Spacy
Document Classification
Data Pipelines
K Means
Recurrent Neural Networks

Requirements

Adidev Technologies is seeking 2 yrs of relevant experience in Data Science. A project can last anywhere from 6 months to 18 months. Salary varies depending on experience, and we are in search of candidates looking to start as soon as possible. Excellent written and oral communication are required as is the ability to work well in a team environment., Demonstrated experience using machine learning, deep learning, statistical methodology, and simulation/optimization modeling in geospatial, network topography, recommendation-systems, environmental systems and/or agronomic problems. Strong foundation in Python programming in a cloud environment. Strong quantitative abilities, distinctive problem-solving, and excellent analysis skills Expertise in data wrangling using SQL, Practical knowledge and experience with cloud-computing systems and platforms, including the routine deployment of pipelines through Kubernetes Fluency in querying/extracting/aggregating data via SQL scripting. Extract, load and transform data (ETL) from structured and unstructured sources Apply Natural Language Processing and Computer Vision to solve business use cases, Strong skills in scientific data analyses, modeling, visualization and communication of results. Knowledge of Python libraries (NumPy, Pandas, SciKit-Learn, TensorFlow, PyTorch), Spacy, MongoDB, PostgreSQL, Flask, streamlet and a good knowledge of data pipelines construction

Must have

Understanding of various machine learning algorithms (e.g. SVM, Random Forests, Gradient Boosting, Log-Log regression, XGBoost, Lasso, Ridge, Clustering techniques, Neural Networks and others) Regression (e.g. ? Linear/Logistic/MNL/Mixed Effects/Regularization) Classification (K-means, Hierarchical, Latent Class, DBScan, SVM) Dimension Reduction techniques (Principal Component analysis, Singular Value Decomposition etc.) Optimization (Linear programming, Stochastic Gradient Descent, Genetic Algorithm etc.) Experience with neural network approaches to text classification CNN, RNN, LSTM,Keras Machine Learning algorithms? Neural Networks, Nave Bayes, Bagging & Boosting, Random Forest Distributed computing tools and cloud technology (AWS)

Benefits & conditions

  • Competitive Salary
  • Paid Relocation
  • Remote Support
  • Guaranteed Regular Salary Reviews
  • Job Type: W2 or Contract 1099 (full-time - 40 hours).

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