Major Responsibilities :

- Research and Problem-Solving : Identify and frame business problems, conduct exploratory data analysis, and propose innovative data science solutions tailored to business needs.

- Leadership & Communication : Serve as a technical referent for the research team, driving high-impact, high-visibility initiatives.

- Effectively communicate complex scientific concepts to senior stakeholders, ensuring insights are actionable for both technical and non-technical audiences.

- Mentor and develop scientists within the team, fostering growth and technical excellence.

- Algorithm Development : Design, optimize, and implement advanced machine learning algorithms, including neural networks, ensemble models (XGBoost, random forests), and clustering techniques.

- End-to-End Project Ownership : Lead the development, deployment, and monitoring of machine learning models and data pipelines for large-scale applications.

- Model Optimization and Scalability : Focus on optimizing algorithms for performance and scalability, ensuring robust, well-calibrated models suitable for real-time environments.

- A/B Testing and Validation : Design and execute experiments, including A/B testing, to validate model effectiveness and business impact.

- Big Data Handling : Leverage tools like BigQuery, advanced SQL, and cloud platforms (e., GCP) to process and analyze large datasets.

- Collaboration and Mentorship : Work closely with engineering, product, and campaign management teams, while mentoring junior data scientists in best practices and advanced techniques.

- Data Visualization : Create impactful visualizations using tools like matplotlib, seaborn, Looker, and Grafana to communicate insights effectively to stakeholders.

Required Experience/Skills :

- 5-8 years of hands-on experience in data science or machine learning roles.

- 2+ years leading data science projects in AdTech.

- Strong hands-on skills in Advanced Statistics, Machine Learning, and Deep Learning.

- Demonstrated ability to implement and optimize neural networks and other advanced ML models.

- Proficiency in Python for developing machine learning models, with a strong grasp of TensorFlow or PyTorch.

- Expertise handling large datasets using advanced SQL and big data tools like BigQuery.

- In-depth knowledge of MLOps pipelines, from data preprocessing to deployment and monitoring.

- Strong background in A/B testing, statistical analysis, and experimental design.

- Proven capability in clustering, segmentation, and unsupervised learning methods.

- Strong problem-solving and analytical skills with a focus on delivering business value.

Education :

- A Master's in Data Science, Computer Science, Mathematics, Statistics, or a related field is preferred.

- A Bachelor's degree with exceptional experience will also be considered.