Job Overview
We are looking for a dynamic and innovative Full Stack Data Engineer with 2+ 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
1. Data Engineering & Preprocessing
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Collect, clean, and preprocess structured and unstructured data from various sources.
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Perform advanced feature engineering, outlier detection, and data transformation.
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Collaborate with data engineers to ensure seamless data pipeline development.
2. Machine Learning Model Development
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Design, train, and validate machine learning models (supervised, unsupervised, deep learning).
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Optimize models for business KPIs such as accuracy, recall, and precision.
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Innovate with advanced algorithms tailored to marketing technologies.
3. Full Stack Development
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Build production-grade APIs for model deployment using frameworks like Flask, FastAPI, or Django.
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Develop scalable and modular code for data processing and ML integration.
4. Deployment & Operationalization
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Deploy models on cloud platforms (AWS, Azure, or GCP) using tools like Docker and Kubernetes.
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Implement continuous monitoring, logging, and retraining strategies for deployed models.
5. Insight Visualization & Communication
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Create visually compelling dashboards and reports using Tableau, Power BI, or similar tools.
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Present insights and actionable recommendations to stakeholders effectively.
6. Collaboration & Teamwork
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Work closely with marketing analysts, product managers, and engineering teams to solve business challenges.
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Foster a collaborative environment that encourages innovation and shared learning.
7. Continuous Learning & Innovation
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Stay updated on the latest trends in AI/ML, especially in marketing automation and analytics.
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Identify new opportunities for leveraging data science in MarTech solutions.
Qualifications
Educational Background
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Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.
Technical Skills
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Programming Languages: Python (must-have), R, or Julia; familiarity with Java or C++ is a plus.
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ML Frameworks: TensorFlow, PyTorch, Scikit-learn, or XGBoost.
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Big Data Tools: Spark, Hadoop, or Kafka.
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Cloud Platforms: AWS, Azure, or GCP for model deployment and data pipelines.
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Databases: Expertise in SQL and NoSQL (e.g., MongoDB, Cassandra).
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Visualization: Mastery of Tableau, Power BI, Plotly, or D3.js.
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Version Control: Proficiency with Git for collaborative coding.
Experience
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2+ years of hands-on experience in data science, machine learning, and software engineering.
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Proven expertise in deploying machine learning models in production environments.
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Experience in handling large datasets and implementing big data technologies.
Soft Skills
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Strong problem-solving and analytical thinking.
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Excellent communication and storytelling skills for technical and non-technical audiences.
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Ability to work collaboratively in diverse and cross-functional teams.
Preferred Qualifications
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Experience with Natural Language Processing (NLP) and Computer Vision (CV).
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Familiarity with CI/CD pipelines and DevOps for ML workflows.
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Exposure to Agile project management methodologies.
Why Join Us?
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Opportunity to work on innovative projects with cutting-edge technologies.
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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!
