Data Scientist - Full Stack Solutions

Job Overview

We are looking for a dynamic and innovative Full Stack Data Scientist with 3+ years of experience who excels in end-to-end data science solutions. The ideal candidate is a tech-savvy professional passionate about leveraging data to solve complex problems, develop predictive models, and drive business impact in the MarTech domain.

Key Responsibilities

• Data Engineering & Preprocessing
• Collect, clean, and preprocess structured and unstructured data from various sources.
• Perform advanced feature engineering, outlier detection, and data transformation.
• Collaborate with data engineers to ensure seamless data pipeline development.
• Machine Learning Model Development
• Design, train, and validate machine learning models (supervised, unsupervised, deep learning).
• Optimize models for business KPIs such as accuracy, recall, and precision.
• Innovate with advanced algorithms tailored to marketing technologies.
• Full Stack Development
• Build production-grade APIs for model deployment using frameworks like Flask, FastAPI, or Django.
• Develop scalable and modular code for data processing and ML integration.
• Deployment & Operationalization
• Deploy models on cloud platforms (AWS, Azure, or GCP) using tools like Docker and Kubernetes.
• Implement continuous monitoring, logging, and retraining strategies for deployed models.
• Insight Visualization & Communication
• Create visually compelling dashboards and reports using Tableau, Power BI, or similar tools.
• Present insights and actionable recommendations to stakeholders effectively.
• Collaboration & Teamwork
• Work closely with marketing analysts, product managers, and engineering teams to solve business challenges.
• Foster a collaborative environment that encourages innovation and shared learning.
• Continuous Learning & Innovation
• Stay updated on the latest trends in AI/ML, especially in marketing automation and analytics.
• Identify new opportunities for leveraging data science in MarTech solutions.
  
  

Qualifications

Educational Background

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.
  
  

Technical Skills

• Programming Languages: Python (must-have), R, or Julia; familiarity with Java or C++ is a plus.
• ML Frameworks: TensorFlow, PyTorch, Scikit-learn, or XGBoost.
• Big Data Tools: Spark, Hadoop, or Kafka.
• Cloud Platforms: AWS, Azure, or GCP for model deployment and data pipelines.
• Databases: Expertise in SQL and NoSQL (e.g., MongoDB, Cassandra).
• Visualization: Mastery of Tableau, Power BI, Plotly, or D3.js.
• Version Control: Proficiency with Git for collaborative coding.
  
  

Experience

• 3+ years of hands-on experience in data science, machine learning, and software engineering.
• Proven expertise in deploying machine learning models in production environments.
• Experience in handling large datasets and implementing big data technologies.
  
  

Soft Skills

• Strong problem-solving and analytical thinking.
• Excellent communication and storytelling skills for technical and non-technical audiences.
• Ability to work collaboratively in diverse and cross-functional teams.
  
  

Preferred Qualifications

• Experience with Natural Language Processing (NLP) and Computer Vision (CV).
• Familiarity with CI/CD pipelines and DevOps for ML workflows.
• Exposure to Agile project management methodologies.
  
  

Why Join Us

• Opportunity to work on innovative projects with cutting-edge technologies.
• Collaborative and inclusive work environment that values creativity and growth.
  
  

If you're passionate about turning data into actionable insights and driving impactful business decisions, we'd love to hear from you!