Senior Data Scientist

Good co India; India; Remote; INR 1,600,000 - 2,400,000; Full time

Job summary

Good co India is seeking an experienced Data Scientist to develop, deploy, and optimize machine learning models that solve complex business problems. You will perform EDA, feature engineering, and statistical analyses on large datasets to build accurate predictive models and time-series forecasts.

You will apply NLP, Generative AI techniques and collaborate with data engineering and software teams to ensure production-grade solutions, with a focus on scalability, governance, and measurable

Qualifications

• Bachelor's or Master's degree in a quantitative field (CS/DS/AI/Stats/Math/Engineering).
• 5–10 years of relevant experience in data science, ML, or analytics.
• Strong Python, SQL, statistics, and data manipulation skills.
• Hands-on with ML libraries (Scikit-learn, TensorFlow, PyTorch).

Responsibilities

• Develop, implement, and optimize ML models to solve business problems.
• Conduct EDA, feature engineering, statistical analysis, and predictive modelling on large datasets.
• Build and evaluate supervised/unsupervised models including time-series forecasting.
• Apply NLP, Generative AI techniques for data-driven solutions.
• Translate business requirements into analytical approaches and measurable outcomes.
• Deploy, monitor, and maintain production-grade models with data/software teams.
• Develop scalable data science workflows using Python, SQL, and cloud tech.
• Perform hypothesis testing, A/B testing, and statistical validation.
• Communicate findings and recommendations to technical and non-technical stakeholders.
• Mentor junior data scientists, conduct code reviews, promote reproducibility.
• Ensure data quality, model reliability, privacy, and governance compliance.
• Stay updated with emerging ML techniques and industry practices.

Skills

Python

SQL

Statistics

EDA

ML deployment

Cloud platforms

MLOps

Docker

CI/CD

Big data

Mentoring

Education

Bachelor's or Master's in CS / Data Science / AI

Tools

Scikit-learn

TensorFlow

PyTorch

Apache Spark

Docker

CI/CD

Job description

Role & responsibilities

• Develop, implement, and optimize machine learning models to solve complex business problems and improve decision-making.
• Perform exploratory data analysis (EDA), feature engineering, statistical analysis, and predictive modelling on large datasets.
• Build and evaluate supervised and unsupervised learning models, including classification, regression, clustering, and time-series forecasting.
• Apply deep learning, NLP, and Generative AI techniques to develop innovative data-driven solutions.
• Translate business requirements into analytical approaches, actionable insights, and measurable outcomes.
• Deploy, monitor, and maintain production-grade machine learning models in collaboration with data engineering and software engineering teams.
• Develop scalable data science workflows and pipelines using Python, SQL, and cloud-based technologies.
• Conduct hypothesis testing, A/B testing, experimentation, and statistical validation to measure model effectiveness.
• Communicate analytical findings, model performance, and recommendations to technical and non-technical stakeholders.
• Mentor junior data scientists, conduct code reviews, and promote best practices in model development, documentation, and reproducibility.
• Ensure data quality, model reliability, explainability, privacy, and compliance with relevant governance standards.
• Stay updated with emerging machine learning techniques, AI technologies, and industry best practices.

Preferred candidate profile

• 5 to 10 years of relevant experience in Data Science, Machine Learning, Advanced Analytics, or a related field.
• Bachelor's or master's degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, Engineering, or a related quantitative discipline.
• Strong proficiency in Python, SQL, statistics, probability, data manipulation, and exploratory data analysis.
• Hands-on experience developing, validating, and deploying machine learning models using libraries such as Scikit-learn, TensorFlow, or PyTorch.
• Strong understanding of feature engineering, model selection, hyperparameter tuning, cross-validation, and model evaluation metrics.
• Experience with NLP, deep learning, Generative AI, LLMs, and RAG architectures is an advantage.
• Working knowledge of cloud platforms such as AWS, Azure, or GCP, along with MLOps, Docker, CI/CD, and model monitoring.
• Experience with big data technologies, data pipelines, and distributed processing frameworks such as Apache Spark is preferred.
• Proven ability to independently manage end-to-end data science projects and deliver measurable business impact.
• Strong analytical thinking, problem-solving, communication, and stakeholder management skills.
• Ability to collaborate with cross-functional teams and mentor junior team members.
• Experience in production model deployment, experimentation, and translating complex analytical results into business recommendations is highly desirable.