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!
