Senior Data Science Manager

Good co India; India; Remote; INR 1,800,000 - 3,200,000; Full time

Job summary

Good co India is seeking a Lead Data Scientist to guide a team of data scientists, ML engineers and analysts in delivering high-impact data science solutions. You will define the roadmap, translate complex business problems into predictive models and insights, and collaborate with product, engineering and leadership to align data initiatives with business goals.

You will establish best practices for model development, experimentation, governance, and responsible AI, drive experimentation and

Qualifications

• 5–10 years of experience in Data Science, ML, or analytics, including leading teams or major initiatives.

Responsibilities

• Lead and manage a team of Data Scientists, ML Engineers, and Data Analysts to deliver high-impact data science solutions.

Skills

Python

SQL

Statistics

Machine learning

A/B testing

MLOps

Cloud platforms

Communication

Leadership

GenAI/NLP

Education

Bachelor's degree in CS/DS/Statistics

Master's degree preferred

Tools

PyTorch

TensorFlow

Scikit-learn

XGBoost

Pandas

NumPy

Job description

Role & responsibilities

• Lead and manage a team of Data Scientists, ML Engineers, and Data Analysts to deliver high-impact data science solutions.
• Define and execute the data science roadmap and strategy aligned with business and product objectives.
• Translate complex business problems into data-driven solutions, predictive models, and actionable insights.
• Lead development of machine learning, statistical, predictive, NLP, recommendation, forecasting, and GenAI models.
• Establish best practices for data exploration, feature engineering, model development, experimentation, validation, and deployment.
• Drive A/B testing, experimentation, causal analysis, and statistical modeling to support product and business decisions.
• Partner with Product, Engineering, Business, Marketing, Finance, and Leadership teams to identify and prioritize opportunities.
• Define and track KPIs, model performance metrics, business impact, and ROI of data science initiatives.
• Oversee the transition of models from research/PoC to reliable production systems in collaboration with ML and Engineering teams.
• Ensure appropriate practices for data quality, model governance, privacy, security, fairness, and responsible AI.
• Review analytical methodologies, statistical approaches, models, and technical deliverables.
• Mentor Data Scientists and develop a strong culture of technical excellence, experimentation, documentation, and knowledge sharing.
• Manage project timelines, resources, priorities, and dependencies across multiple data science initiatives.
• Evaluate emerging AI/ML, GenAI, and analytics technologies and identify opportunities for business adoption.
• Present complex analytical findings and recommendations clearly to senior leadership and non-technical stakeholders.

Preferred candidate profile

• 5 to 10 years of experience in Data Science, Machine Learning, Advanced Analytics, or a related field, including experience leading teams or major data science initiatives.
• Strong expertise in Python, SQL, statistics, probability, machine learning, and predictive modeling.
• Strong understanding of supervised/unsupervised learning, feature engineering, model evaluation, optimization, and statistical inference.
• Experience with PyTorch, TensorFlow, Scikit-learn, XGBoost, Pandas, NumPy, or equivalent tools.
• Experience with A/B testing, experimentation, hypothesis testing, causal inference, and product/business analytics.
• Knowledge of Generative AI, LLMs, NLP, recommendation systems, time-series forecasting, or other advanced ML techniques is highly desirable.
• Experience with cloud platforms such as AWS, Azure, or GCP and modern data/ML platforms such as Databricks or Snowflake.
• Working knowledge of MLOps, MLflow, model deployment, model monitoring, and production ML workflows.
• Strong understanding of data engineering, ETL/ELT, data warehouses, data lakes, and distributed data processing.
• Proficiency with visualization and BI tools such as Tableau, Power BI, Looker, or equivalent.
• Demonstrated ability to lead cross-functional projects and mentor/manage Data Science teams.
• Strong business acumen with the ability to connect analytical work to revenue, cost reduction, customer experience, risk, or other measurable business outcomes.
• Excellent communication, stakeholder management, strategic thinking, and presentation skills.
• Bachelor's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, Economics, or a related quantitative field; Master's degree preferred.
• Experience with responsible AI, data governance, model governance, and data privacy is an advantage.