Lead Data Scientist

Good co India; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Good co India in United States seeks an experienced Data Scientist to lead end-to-end ML initiatives, translate business problems into data-driven solutions, and deploy production-grade models. You will work with large datasets, collaborate across teams, and mentor junior data scientists to advance best practices.

The role requires strong Python/SQL skills, a solid foundation in statistics and experimental design, and hands-on experience with ML, NLP, Generative AI, and LLMs.

Qualifications

• 5 to 10 years of relevant experience in Data Science, Machine Learning, AI, or a related quantitative field.
• Strong proficiency in Python and SQL, with hands-on experience in machine learning and statistical modeling.
• Strong foundation in statistics, probability, machine learning, and experimental design.
• Experience building and deploying production-grade ML models and data products.
• Hands-on experience with deep learning, NLP, Generative AI, or LLMs is preferred.
• Experience with cloud platforms such as AWS, Azure, or GCP and modern data/ML platforms.
• Familiarity with MLOps tools and practices, including MLflow, Docker, CI/CD, model monitoring, and model deployment.
• Experience working with large-scale data using technologies such as Spark, Databricks, or equivalent platforms.
• Strong problem-solving, analytical, communication, and stakeholder-management skills.
• Demonstrated ability to lead projects independently and mentor other data scientists.
• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Economics, or another quantitative discipline.
• Strong business acumen with the ability to connect technical solutions to measurable business outcomes.

Responsibilities

• Lead the design, development, and deployment of advanced machine learning and data science solutions.
• Translate complex business problems into data-driven solutions and actionable insights.
• Develop and optimize predictive models, statistical models, and AI/ML algorithms.
• Work with large and complex datasets to identify trends, patterns, and business opportunities.
• Lead end-to-end data science projects, from problem formulation and experimentation to production deployment.
• Collaborate with engineering, product, business, and analytics teams to deliver scalable solutions.
• Mentor and guide junior and mid-level data scientists and contribute to technical best practices.
• Design and evaluate experiments, A/B tests, and model performance metrics.
• Apply modern AI techniques, including deep learning, NLP, Generative AI, and LLM-based solutions where relevant.
• Establish best practices for model development, validation, deployment, monitoring, and MLOps.
• Present technical findings, model results, and business recommendations to senior stakeholders.
• Stay current with emerging developments in AI, machine learning, data science, and cloud technologies.

Skills

Python

SQL

Statistics

Experimental design

Data science

Machine learning

NLP

Generative AI

LLMs

MLOps

Spark

Databricks

CI/CD

Docker

Education

Bachelor's or Master's in a quantitative field

Tools

Spark

Databricks

MLflow

Docker

CI/CD

Job description

Role & responsibilities

• Lead the design, development, and deployment of advanced machine learning and data science solutions.


• Translate complex business problems into data-driven solutions and actionable insights.


• Develop and optimize predictive models, statistical models, and AI/ML algorithms.


• Work with large and complex datasets to identify trends, patterns, and business opportunities.


• Lead end-to-end data science projects, from problem formulation and experimentation to production deployment.


• Collaborate with engineering, product, business, and analytics teams to deliver scalable solutions.


• Mentor and guide junior and mid-level data scientists and contribute to technical best practices.


• Design and evaluate experiments, A/B tests, and model performance metrics.


• Apply modern AI techniques, including deep learning, NLP, Generative AI, and LLM-based solutions where relevant.


• Establish best practices for model development, validation, deployment, monitoring, and MLOps.


• Present technical findings, model results, and business recommendations to senior stakeholders.


• Stay current with emerging developments in AI, machine learning, data science, and cloud technologies.

Preferred candidate profile

• 5 to 10 years of relevant experience in Data Science, Machine Learning, AI, or a related quantitative field.


• Strong proficiency in Python and SQL, with hands-on experience in machine learning and statistical modeling.


• Strong foundation in statistics, probability, machine learning, and experimental design.


• Experience building and deploying production-grade ML models and data products.


• Hands-on experience with deep learning, NLP, Generative AI, or LLMs is preferred.


• Experience with cloud platforms such as AWS, Azure, or GCP and modern data/ML platforms.


• Familiarity with MLOps tools and practices, including MLflow, Docker, CI/CD, model monitoring, and model deployment.


• Experience working with large-scale data using technologies such as Spark, Databricks, or equivalent platforms.


• Strong problem-solving, analytical, communication, and stakeholder-management skills.


• Demonstrated ability to lead projects independently and mentor other data scientists.


• Bachelors or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Economics, or another quantitative discipline.


• Strong business acumen with the ability to connect technical solutions to measurable business outcomes.