Senior / Lead Data Scientist

Role Summary

As a Senior / Lead Data Scientist, you will drive advanced analytics and machine learning initiatives across high-impact products and data platforms. You will work with cross-functional teams to translate business challenges into scalable, production-ready data models, lead data science strategy, and uplift technical standards across projects. Your experience in large-scale systems, real-time processing, and deep learning will help shape the deployment of next-generation predictive and AI solutions.

Key Responsibilities

• Lead full lifecycle development of data science and ML solutions from data exploration through model development, evaluation, and production deployment.
• Design and implement machine learning, deep learning, and statistical models to solve business problems including predictive analytics, anomaly detection, and customer/user behavior insights.
• Leverage advanced tools such as TensorFlow, PyTorch, H2O.ai, Spark, and other modern frameworks to build robust, scalable solutions.
• Architect real-time and batch pipelines using tools like Apache Kafka, Apache Flink, Hadoop, Spark, and cloud services (AWS/Azure/Google Cloud Platform).
• Apply AutoML, interpretable machine learning, and explainability techniques to ensure model reliability, fairness, and regulatory compliance.
• Build interactive dashboards and visualization tools to present insights effectively to stakeholders.
• Partner with engineering and product teams to integrate models into applications and production workflows.
• Mentor and coach data science and analytics teams, promoting best practices in modeling, experimentation, and model monitoring.
• Support strategic decision-making by communicating complex concepts to technical and non-technical leadership.

Required Qualifications

• 15+ years of professional experience in data science, analytics, or related fields.
• Extensive expertise in advanced machine learning and deep learning methods.
• Strong programming experience in Python (Tensor Flow, PyTorch), Scala/Java, SQL, and familiarity with visualization libraries like D3.js.
• Proven experience with big data ecosystems and distributed computing.
• Practical deployment experience with cloud-based infrastructure (AWS, Azure, Google Cloud Platform) and real-time data processing.
• Track record of delivering data science solutions that drove measurable business outcomes.
• Demonstrated ability to mentor, lead technical discussions, and influence cross-disciplinary teams.

Preferred Qualifications

• Experience in enterprise environments and Fortune-level engagements.
• Knowledge of NLP, time series forecasting, and deep learning applications.
• Excellent communication and stakeholder-management skills.