Job Description

Data Scientist/ML-Ops - 1

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.

? 4+ 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

Job Type: Contractual / Temporary
Contract length: 3-6 months

Pay: ?80,000.00 - ?90,000.00 per month

Schedule:

Day shift Monday to Friday
Application Question(s):

Do you have Strong knowledge of probability distributions, statistical inference, and GLMs. Do you have 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). Do you have Understanding of MLOps principles and API integration.
Experience:

Data science: 5 years (Required)
Work Location: Remote