Senior Full Stack Data Scientist

Senior Full Stack Data Scientist

Senior Full Stack Data Scientist

business goals and consistently deliver measurable impact. 

About the Team

scalable, high-impact

technologies to tackle real business challenges. 

Key Responsibilities

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.

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. 

end-to-end data solutions