Senior Data Scientist - ML, Python
San Antonio , TX
Exp: 12+ Years
MUST HAVE
- Strong expertise in data science, machine learning, and statistical modeling.
- Proficiency in tools and languages such as Python, SQL, pySpark, ML packages.
- Expertise in building – XGBoost type classification models and ARIMA/SARIMA type forecasting models
- Bachelor's or Master's degree in Mathematics, Physics, Data Science, Statistics, AI/ML
- Good experience in quantitative analytics or data science
Job responsibilities:
- Responsible for coding and testing customized analytical models of medium to high degree of complexity.
- Must be able to implement best practices when writing and testing code.
- Familiarity with the life cycle of a data science project and extensive experience with python and XGboost , Arima/Sarima is a must .
- Requires strong interpersonal and communication skills, operational Elasticsearch knowledge and ability to construct GUI interfaces
- Gathers, interprets, and manipulates structured and unstructured data to enable analytical solutions for the business.
- Selects the appropriate modeling technique and/or technology with consideration to data limitations, application, and business needs
- Proven experience in developing models using Regression, Decision trees, Bayesian networks, Random Forest, Logistic regression, Support vector machine, Gradient boosting algorithms, Clustering algorithms and Dimensionality Reduction Algorithms.
- Proven experience in building and implementing Timeseries and forecasting models.
- Experience in Deep Learning model development using TensorFlow, Keras, PyTorch
- Hands on experience in building ML workflows
- Experience in Model implementation, Governance, and monitoring.
- Responsibilities include Performing the code development of complex analytic algorithms and paradigms, perform a clear breakdown of the analytic functionality and separate it into working modules.
- Working experience in Python, R and SQL
- Experience in Python data science packages such as numPy, SciPy and SciKit-learn
Nice to Have:
- Fluent with Natural Language Processing and text analytics libraries (NLTK, SpaCy)
- Experience with Data Science Platforms (Dataiku, H2o, Azure...)
- Experience with one of Subversion/ SVN, Git, GitHub, GitLab, Mercurial, or other version control system
- Experience with cloud platforms AWS, Azure, GCP a plus
- Knowledge in Big Data, Hadoop, HIVE/HQL, HDFS, Spark/PySpark, Kafka
- Familiar working in an AGILE environment