Data Scientist
Job in
Boise, Ada County, Idaho, 83701, USA
Listed on 2026-11-01
Listing for:
Akaasa Infotech Noida
Part Time
position Listed on 2026-11-01
Job specializations:
-
IT/Tech
Data Scientist, Machine Learning/ ML Engineer, Data Analyst, Data Engineering
Job Description & How to Apply Below
Job Title:
Data Scientist
Experience: 7+ Years
Employment Type:
Contractual
Work Mode: 100% Remote
Location:
Remote, India
- UK Shift: 1:00 PM 10:00 PM IST
- US EST Shift: 5:30 PM 2:30 AM IST
- Candidates must be comfortable working in either shift, depending on project requirements.
We are looking for an experienced Data Scientist with 7+ years of expertise in data analytics, statistical modeling, and machine learning. The candidate will analyze complex datasets, develop predictive models, and deliver actionable business insights.
Key Responsibilities- Collect, clean, preprocess, and analyze large datasets.
- Develop statistical models, predictive analytics solutions, and machine learning algorithms.
- Perform exploratory data analysis, feature engineering, and model validation.
- Apply regression, classification, clustering, and forecasting techniques.
- Use Python and SQL to extract insights and solve business problems.
- Develop data visualizations and communicate findings to stakeholders.
- Collaborate with data engineers and ML engineers to deploy data-driven solutions.
- Monitor model performance and optimize accuracy and scalability.
- 7+ years of relevant experience in Data Science, analytics, or a related field.
- Strong proficiency in Python, Pandas, Num Py, and Scikit-learn.
- Advanced SQL and database querying skills.
- Strong knowledge of statistics, probability, and predictive modeling.
- Hands-on experience in machine learning, feature engineering, and model evaluation.
- Experience with visualization tools such as Power BI, Tableau, or Matplotlib.
- Exposure to cloud platforms such as AWS, Azure, or GCP.
- Experience with Tensor Flow or PyTorch.
- Knowledge of big data technologies and MLOps practices.
- Experience deploying models in production environments.
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