Data Scientist
Posted on May 22, 2025
Job Description
- Job Description: Data Scientist with a strong foundation in statistics and machine learning.
- Position: Data Scientist
- Shift-timing : India time zone is fine. The resources will need to extend their timings till about 9PM to accommodate any meetings etc
- Location: Remote
- Duration: 6-8 Months (Contract)
- Experience: Mid-Level
- Job Overview:
- We are seeking a detail-oriented Mid-Level Data Scientist with a strong foundation in statistics and machine learning. This role is perfect for someone who thrives on solving complex problems through data, building interpretable models, and integrating insights into production systems. You will collaborate closely with engineering and MLOps teams to ensure your models drive meaningful business impact.
- Key Responsibilities:
- Design, develop, and validate statistical models for classification, regression, and risk assessment.
- Conduct exploratory data analysis (EDA) to uncover patterns, correlations, and insights.
- Build and interpret generalized linear models (GLMs), decision trees, and non-parametric estimators.
- Implement machine learning algorithms such as Logit/Probit, XGBoost, gradient boosting, and quasi-linear methods.
- Generate insights and communicate findings to non-technical stakeholders.
- Collaborate with data engineers to integrate models into production pipelines via APIs.
- Participate in MLOps processes to ensure seamless model deployment and monitoring.
- Provide actionable recommendations based on model outputs to improve business outcomes.
- Required Qualifications:
- Bachelor's degree in Statistics, Mathematics, Data Science, or a related field.
- 2+ years of experience in data science, machine learning, or statistical modeling.
- Strong knowledge of probability distributions, statistical inference, and GLMs.
- Hands-on experience with Probit/Logit, XGBoost, decision trees, and non-parametric methods.
- Proficiency in Python for data analysis and model development (NumPy, Pandas, SciPy).
- Understanding of MLOps principles and API integration.
- Excellent communication and presentation skills.
- Preferred Qualifications:
- Familiarity with TensorFlow, Keras, or PyTorch for machine learning.
- Experience with data visualization tools like Matplotlib or Seaborn.
- Basic understanding of cloud-based ML platforms (Azure, AWS, GCP).
- Knowledge of data engineering best practices for model deployment.
Required Skills
2+ years of experience in data science
machine learning
or statistical modeling. strong knowledge of probability distributions
statistical inference
and glms. hands-on experience with probit/logit
xgboost
decision trees
and non-parametric methods. proficiency in python for data analysis and model development (numpy
pandas
scipy). understanding of mlops principles and api integration.