Marketing Automation Specialist

HCL Software (hcl-software.com) delivers software that fulfils the transformative needs of clients around the world. We build award winning software across AI, Automation, Data & Analytics, Security and Cloud.

The HCL Unica+ Marketing Platform enables our customers to deliver precision and high performance Marketing campaigns across multiple channels like Social Media, AdTech Platforms, Mobile Applications, Websites, etc. The Unica+ Marketing Platform is a Data and AI first platform that enables our clients to deliver hyper-personalized offers and messages for customer acquisition, product awareness and retention.

We are seeking a Senior Architect Developer with strong Data Science and Machine Learning skills and experience to deliver AI driven Marketing Campaigns.

Responsibilities

1. Designing and Architecting End-to-End AI/ML Solutions for Marketing:

   The architect is responsible for designing robust, scalable, and secure AI/ML solutions specifically tailored for marketing challenges. This includes defining data pipelines, selecting appropriate machine learning algorithms and frameworks (e.g., for predictive analytics, customer segmentation, personalization, campaign optimization, sentiment analysis), designing model deployment strategies, and integrating these solutions seamlessly with existing marketing tech stacks and enterprise systems. They must consider the entire lifecycle from data ingestion to model monitoring and retraining.

2. Technical Leadership:

   The AI/ML architect acts as a technical leader, providing guidance and mentorship to data scientists, ML engineers, and other development teams. They evaluate and select the most suitable AI/ML tools, platforms, and cloud services (AWS, GCP, Azure) for marketing use cases. The architect is aso responsible for establishing and promoting best practices for MLOps (Machine Learning Operations), model versioning, continuous integration/continuous deployment (CI/CD) for ML models, and ensuring data quality, ethical AI principles (e.g., bias, fairness), and regulatory compliance (e.g., data privacy laws).
3. Python Programming & Libraries: Proficient in Python with extensive experience using Pandas for data manipulation, NumPy for numerical operations, and Matplotlib/Seaborn for data visualization.
4. Statistical Analysis & Modelling: Strong understanding of statistical concepts, including descriptive statistics, inferential statistics, hypothesis testing, regression analysis, and time series analysis.
5. Data Cleaning & Preprocessing: Expertise in handling messy real-world data, including dealing with missing values, outliers, data normalization/standardization, feature engineering, and data transformation.
6. SQL & Database Management: Ability to query and manage data efficiently from relational databases using SQL, and ideally some familiarity with NoSQL databases.
7. Exploratory Data Analysis (EDA): Skill in visually and numerically exploring datasets to understand their characteristics, identify patterns, anomalies, and relationships.
8. Machine Learning Algorithms: In-depth knowledge and practical experience with a wide range of ML algorithms such as linear models, tree-based models (Random Forests, Gradient Boosting), SVMs, K-means, and dimensionality reduction techniques (PCA).
9. Deep Learning Frameworks: Proficiency with at least one major deep learning framework like TensorFlow or PyTorch. This includes understanding neural network architectures (CNNs, RNNs, Transformers) and their application to various problems.
10. Model Evaluation & Optimization: Ability to select appropriate evaluation metrics (e.g., precision, recall, F1-score, AUC-ROC, RMSE) for different problem types, diagnose model performance issues (bias-variance trade-off), and apply optimization techniques.
11. Deployment & MLOps Concepts: Deploy machine learning models into production environments, including concepts of API creation, containerization (Docker), version control for models, and monitoring.

Qualifications & Skills

1. At least 15+ years of Experience across Data Architecture, Data Science and Machine Learning.
2. Experience in delivering AI/ML models for Marketing Outcomes like Customer Acquisition, Customer Churn, Next Best Product or Offer. This is a mandatory requirement.
3. Experience with Customer Data Platforms (CDP) and Marketing Platforms like Unica, Adobe, SalesForce, Braze, TreasureData, Epsilon, Tealium is mandatory.
4. Experience with AWS SageMaker is advantageous
5. Experience with LangChain, RAG for Generative AI is advantageous.
6. Experience with ETL process and tools like Apache Airflow is advantageous
7. Expertise in Integration tools and frameworks like Postman, Swagger, API Gateways
8. Ability to work well within an agile team environment and apply the related working methods.
9. Excellent communication & interpersonal skills
10. A 4-year degree in Computer Science or IT is a must.

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