We are seeking a seasoned Senior Data Scientist with 58 years of experience who can take ownership of end-to-end data science solutions, from conceptualizing and researching business problems to designing and optimizing algorithms, implementing solutions, and monitoring their
performance. This role requires a strong ability to translate complex business challenges into data-driven solutions, work collaboratively across teams, and deliver measurable business impact.
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.
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.g., 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:
58 years of hands-on experience in data science or machine learning roles.
Proficiency in Python for developing machine learning models, with a strong grasp of TensorFlow or PyTorch.
Expertise in handling large datasets using advanced SQL and big data tools like BigQuery.
In-depth knowledge of machine learning pipelines, from data preprocessing to deployment and monitoring.
Strong background in A/B testing, statistical analysis, and experimental design.
Demonstrated ability to implement and optimize neural networks and other advanced ML models.
Experience in developing scalable data pipelines and deploying models in production environments.
Proven capability in clustering, segmentation, and unsupervised learning methods.
Preferred Skills:
Familiarity with MLOps practices, including CI/CD pipelines for machine learning.
Knowledge of advanced AI techniques, such as reinforcement learning or natural language processing.
Experience working with business intelligence tools and creating actionable dashboards.
Strong problem-solving and analytical skills with a focus on delivering business value.
Education:
A Masters in Data Science, Computer Science, Mathematics, Statistics, or a related field is preferred. A Bachelor's degree with exceptional experience will also be considered.
