Senior Data Scientist & ML Engineer — Python, SQL, Cloud

Simarn Solutions; United States; On-site; USD 150,000 - 190,000; Full time

Job summary

Simarn Solutions is seeking a Data Scientist / Machine Learning Engineer with 9–10 years of experience to develop and deploy data science and machine-learning solutions. Strong Python, SQL and cloud-based analytics platform skills are required to support the full ML lifecycle.

The ideal candidate will perform data exploration, feature engineering, model development, validation and productionization of ML solutions in a cloud environment.

Qualifications

• 9–10 years of Data Science / Machine Learning experience.
• Hands-on Python for data science and ML.
• Strong SQL for data analysis and data preparation.
• Knowledge of ML and statistical modeling.
• Experience with data preparation, exploration, and preprocessing.
• Experience with feature engineering for ML models.
• Experience with model development, validation, and evaluation.
• Experience with productionization and deployment of ML solutions.
• Experience with cloud-based data platforms.
• Understanding end-to-end ML lifecycle.

Responsibilities

• Develop and deploy data science and machine-learning solutions.
• Perform data exploration and feature engineering.
• Develop and implement machine-learning and statistical models.
• Perform model validation and evaluation.
• Prepare and process data for machine-learning solutions.
• Productionize machine-learning and data science solutions.
• Work with Python and SQL for data analysis and modeling.
• Utilize cloud-based data/analytics platforms to support data science and machine-learning solutions.

Skills

Python for ML

SQL

Data exploration

Feature engineering

Model validation

Model deployment

Cloud platforms

End-to-end ML lifecycle

Job description

Simarn Solutions is seeking a Data Scientist / Machine Learning Engineer with 9–10 years of experience to develop and deploy data science and machine-learning solutions. Strong Python, SQL and cloud-based analytics platform skills are required to support the full ML lifecycle.

The ideal candidate will perform data exploration, feature engineering, model development, validation and productionization of ML solutions in a cloud environment.