Senior Data Scientist

About the Role

Key Responsibilities

• Leads multiple data science projects ensuring alignment with business goals.
• Develops predictive models and integrates them with Business Intelligence tools.
• Develops and maintains data pipelines for efficient data retrieval and processing.
• Collaborates with applications and data engineering teams for deploying models at scale.
• Mentors junior data scientists in model development and data handling.
• Engages with Senior Leadership to inform strategic decisions using business intelligence insights.
• Researches and adopts cutting-edge technologies and methodologies in data science.
• Manages stakeholder expectations and delivers actionable solutions.
• Oversees data processing pipelines ensuring data quality and consistency.
• Drives ethical considerations in model deployment and data utilization.
• Collaborates with external partners, research institutions, and subject matter experts to gather domain-specific knowledge and datasets.
• Performs exploratory data analysis to identify patterns, insights, and communicate findings.
• Engages in the ideation and prototyping of new solutions to meet emerging business requirements.
• Utilizes advanced machine learning techniques (e.g., deep learning, NLP, computer vision, reinforcement learning) to create innovative solutions.

Requirements

• Bachelor's Degree in Information Technology or related field.
• 5+ years of relevant experience.
• Expertise in Python and proficiency in ML frameworks (TensorFlow, PyTorch, scikit-learn).
• Deep understanding of ML algorithms (supervised, unsupervised learning, and deep learning) and their applications.
• Strong problem-solving, critical thinking, and analytical capabilities.
• Understanding of AI/ML concepts, algorithms, and platforms.
• Knowledge of business processes, industry trends, and market dynamics.
• Excellent communication skills for stakeholder interaction and collaboration.
• Experience with data mining, extraction, and analysis techniques.
• Proficiency in natural language processing and statistical analysis.

Nice to Have

• Experience with data monetization strategies and techniques.
• Familiarity with data commercialization, data marketplaces, and data value realization.
• Experience with web mining and customer relationship management (CRM).
• Knowledge of data ethics and responsible innovation practices.
• Experience with reporting and dashboarding tools.

Qualifications

• Bachelor's degree in Information Technology or related field.
• Master's or Ph.D. in Computer Science, Statistics, Mathematics, or related field (preferred).

Benefits & Perks

• Access to health, vision, and dental insurance.
• Paid time off and paid parental leave.
• 401k matching program.
• Educational reimbursement.
• Discretionary company-sponsored annual bonus.
• Total rewards including work environment benefits.