Data Scientist (Full Stack)

Senior Full Stack Data Scientist 

We are seeking a Senior Full Stack Data Scientist who can own the entire lifecycle of data-driven solutions—from data collection and transformation to model deployment and ongoing maintenance. This role requires deep technical expertise, as well as strong communication and leadership skills, to ensure that analytics initiatives align with 

business goals and consistently deliver measurable impact. 

About the Team 

Our data function is a multidisciplinary group of data scientists, engineers, and analysts working together to produce scalable, high-impact data products. We foster a culture of innovation, collaboration, and continuous learning, using state-of-the-art 

technologies to tackle real business challenges. 

Key Responsibilities 

1. End-to-End Data Product Ownership 

• Design and manage full-stack data solutions from data ingestion (ETL/ELT) to model deployment and performance monitoring. 
• Work with business stakeholders to define project scopes, translate ambiguous requirements into actionable data science tasks, and deliver results. 

1. Advanced Analytics s Machine Learning 

• Develop and implement statistical and ML models (e.g., predictive modeling, classification, clustering, time-series forecasting). 
• Employ advanced ML techniques such as Bayesian methods, reinforcement learning, or metaheuristics, as needed. 
• Integrate data science workflows with analytics platforms (e.g., Spark, Dask) for large-scale or real-time processing. 

Software Engineering s DevOps 

• Follow OOP principles and design patterns in Python for clean, maintainable code. 
• Set up CI/CD pipelines, containerization (Docker), and orchestration (Kubernetes) to enable robust, automated deployments. 
• Optimize performance and manage cost on cloud platforms (Azure, AWS, or GCP) by structuring resources effectively. 

Front-End s Visualization 

• Build or enhance user-facing dashboards using frameworks like Streamlit, Plotly Dash, or enterprise solutions (e.g., PowerBI). 
• Present actionable insights in a clear, interactive format that resonates with non-technical audiences. 

Real-Time s Large-Scale Data Architecture 

• Design pipelines for real-time data streaming (e.g., Kafka, Spark Streaming) where business needs require continuous data updates. 
• Work with data engineers to maintain data lakes or data warehouses, ensuring efficient storage and retrieval for diverse use cases. 

Security s Compliance 

• Adhere to data governance and regulatory guidelines (GDPR, HIPAA, etc.) relevant to your industry. 
• Implement secure coding practices and access controls to protect sensitive data assets. 

Performance Tuning s Cost Optimization 

• Continuously monitor, profile, and refine data pipelines and ML models to ensure minimal latency and reduced computational costs. 
• Utilize cloud-native monitoring tools (Azure Monitor, AWS CloudWatch, GCP Stackdriver) for alerts, logging, and budget management. 

Mentorship s Leadership 

• Provide technical guidance and coaching to junior data scientists and data engineers, encouraging best practices. 
• Lead architecture and design reviews, fostering a culture of quality and collaboration across the data organization. 

What We Look For 

• Education s Experience 
• MS or PhD in Computer Science, Statistics, Mathematics, Artificial Intelligence, or a related field. 
• 8+ years of experience delivering end-to-end data solutions in data science, analytics, or machine learning. 
•  Technical Expertise 
• Proficiency in Python, with strong skills in OOP, design patterns, and software engineering best practices. 
• Mastery of ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch) and proficiency in NumFOCUS libraries (pandas, NumPy, SciPy). 
• Familiarity with cloud platforms (Azure, AWS, GCP), containerization (Docker), and orchestration (Kubernetes). 
• Experience with version control (Git) and building CI/CD pipelines for data and ML products. 
• Ability to handle large-scale data (Spark, Dask, or similar) and real-time streaming (Kafka, Flink) when required. 
• Analytical s Communication Skills 
• Deep knowledge of statistics, machine learning, and optimization techniques, paired with the ability to convey technical results to diverse audiences. 
• Experience in data visualization and dashboard creation, conveying complex information in an understandable manner. 
• Proven record of collaborating across business, engineering, and product management teams. 
• Soft Skills s Mindset 
• Commitment to continuous learning and staying current with emerging data science and engineering trends. 
• Strong leadership qualities with a knack for mentoring, problem-solving, and managing stakeholder expectations. 
• Flexible and agile approach to adapting in a fast-paced environment and delivering high-quality outputs. 

Why Join Us 

• Strategic Impact: Work on mission-critical projects where data science informs key decisions and directly influences the bottom line. 
• Cutting-Edge Technology: Leverage a modern tech stack and ample freedom to experiment with new tools and methodologies. 
•  Leadership s Growth: Shape the technical direction of the data organization, mentoring talent and establishing best practices. 
• Collaborative Environment: Join a supportive team culture that values shared learning, innovation, and collective problem-solving. 
• Work-Life Balance: Enjoy a flexible schedule with remote-friendly policies and competitive compensation. 

If you’re passionate about end-to-end data solutions and have the depth of expertise to drive data projects from conception through deployment, we invite you to become our Senior Full Stack Data Scientist. Bring your blend of data science, software engineering, and strategic thinking to propel our organization toward data-driven excellence. Apply now to embark on this exciting journey!