Happiest Minds Technologies - Senior Data Scientist/Manager - ETL/Python

Job Summary :

We are looking for an experienced Senior Data Scientist Manager to lead data science initiatives, manage a team of data scientists, and drive the development and deployment of advanced analytical and machine learning solutions.

The role will work closely with business and technology stakeholders to translate complex business problems into scalable, data-driven solutions.

Key Responsibilities :

1. Data Science Strategy & Leadership :

- Define and execute the data science roadmap aligned with business objectives.

- Lead multiple data science projects from problem definition through deployment and business adoption.

- Identify high-impact opportunities where advanced analytics and machine learning can create measurable business value.

- Establish best practices for experimentation, modelling, validation, and deployment.

- Drive adoption of data-driven decision-making across business functions.

2. Team Management & Capability Building:

- Lead, mentor, and develop a team of data scientists and machine learning professionals.

- Define technical goals, project priorities, and delivery expectations.

- Conduct regular performance reviews and provide technical mentorship.

- Build a strong culture of experimentation, innovation, collaboration, and engineering excellence.

- Support hiring and development of data science talent.

3. Machine Learning & Advanced Analytics:

- Guide teams in developing predictive models, classification models, recommendation systems, forecasting solutions, and other advanced analytical models.

- Review model approaches, feature engineering, statistical techniques, and validation methodologies.

- Ensure models are robust, scalable, explainable, and aligned with business requirements.

- Drive model performance optimization and continuous improvement.

- Establish appropriate model monitoring and performance measurement frameworks.

4. Business & Stakeholder Management:

- Partner with product, engineering, business, and leadership teams to identify and prioritize data science use cases.

- Translate complex analytical findings into actionable business recommendations.

- Present insights, model outcomes, and business impact to senior stakeholders.

- Manage expectations, timelines, dependencies, and delivery priorities across multiple initiatives.

5. Data Science Engineering & Deployment:

- Collaborate with engineering teams to productionize machine learning models and analytical solutions.

- Promote scalable ML pipelines, reproducible experimentation, and automated model deployment.

- Ensure appropriate monitoring, governance, documentation, and lifecycle management of models.

- Drive adoption of MLOps practices across the data science function.

Required Skills & Qualifications:

- 9 - 15 years of experience in Data Science, Machine Learning, Advanced Analytics, or related fields.

- Strong experience leading data science teams and large-scale analytical initiatives.

- Excellent understanding of statistics, machine learning, predictive modelling, and experimentation.

- Strong hands-on experience with Python, SQL, Pandas, NumPy, Scikit-learn and relevant ML frameworks.

- Experience with cloud-based data and ML platforms is preferred.

- Strong understanding of model deployment, MLOps, and production analytics.

- Excellent stakeholder management, communication, and leadership skills.