AEM Forms Designer

Role & Responsibilities

·      Collect, clean, and analyze large structured and unstructured datasets from multiple internal and external sources

·      Conduct thorough exploratory data analysis (EDA) to understand data distributions, relationships, outliers, and missing value patterns

·      Profile and audit datasets to assess data quality, completeness, consistency, and fitness for modeling

·      Investigate and document data lineage — understanding where data originates, how it flows, and how it transforms across systems

·      Identify and resolve data anomalies, inconsistencies, and integrity issues in collaboration with data engineering teams

·      Develop a deep understanding of the business domain and the underlying data that represents it — including what each field means, how it is captured, and what its limitations are

·      Translate raw, messy, real-world data into clean, well-understood analytical datasets ready for modeling and reporting

·      Apply statistical techniques such as correlation analysis, hypothesis testing, variance analysis, and distribution fitting to extract meaningful signals from noise

·      Build and deploy machine learning models including regression, classification, clustering, NLP, and time-series analysis

·      Design, evaluate, and analyze A/B experiments and controlled tests using causal inference techniques

·      Develop data-driven recommendations backed by rigorous statistical reasoning

·      Write clean, production-ready code in Python or R

·      Collaborate with data engineers to build reliable data pipelines and feature stores

·      Deploy and monitor ML models using MLOps best practices on cloud infrastructure

·      Build dashboards and self-serve analytics tools to support stakeholder decision-making

Data Understanding & Analysis Skills

·      Strong ability to interrogate unfamiliar datasets and quickly develop a working understanding of their structure, semantics, and quirks

·      Experience working with messy, incomplete, or poorly documented real-world data

·      Skilled in identifying hidden patterns, trends, seasonality, and anomalies through visual and statistical exploration

·      Ability to ask the right questions about data — challenging assumptions, validating sources, and understanding the context in which data was collected

·      Proficiency in data profiling, descriptive statistics, and summary reporting to communicate the shape and health of a dataset

·      Experience creating data dictionaries, documentation, and data quality reports to support team-wide data understanding

·      Comfort working across structured (relational tables), semi-structured (JSON, XML), and unstructured (text, logs, sensor streams) data formats

Technical Skills Required

·      Proficiency in Python (pandas, NumPy, scikit-learn, PyTorch or TensorFlow) and/or R

·      Strong SQL skills with hands-on experience in DB2 and SQL Server

·      Experience with Databricks for large-scale data processing, feature engineering, and model training

·      Familiarity with cloud platforms: Azure or AWS

·      Experience with data warehouses and big data platforms (Databricks, Snowflake, or Redshift)

·      Knowledge of MLOps tools such as MLflow, Kubeflow, or Airflow

·      Experience with streaming data technologies such as Kafka or Spark

·      Solid foundation in probability, statistics, linear algebra, and experimental design

Nice to Have

·      Experience with deep learning, NLP, computer vision, or Bayesian methods

·      Familiarity with real-time or streaming data pipelines

·      Open-source contributions or published research

Job Responsibilities:

• Be a part of a team developing a rapidly growing product used by thousands of small businesses.
• Responsible for building large scale applications that are high performance, scalable, and resilient in an microservices environment
• Evaluate new technologies and tools such as new frameworks, methodologies, best practices and other areas that will improve overall efficiencies and product quality

Skill Set:

• 3+ years of working experience in developing API centric core Java/J2EE applications using Spring boot, JPA, REST API, XML and JSON
• Experience in frontend framework - any one of Backbone, Angular, Vue or React
• Working experience in any one of the Cloud Platforms - Google Cloud (preferable) or AWS
• Experience in large scale databases - NoSQL and MongoDB.
• Hands on experience in Eclipse based development and using Git, SVN, Junit
• Past experience in startups or product development is a big plus.

High Level Scope of Work :

• Work with AI / Analytics team to priorities MACHINE LEARNING Identified USE CASES for Development and Rollout
• Meet and understand current retail / Marketing Requirements and how AI/ML solution will address and automate the decision process.
• Develop AI/ML Programs using DATAIKU Solution & Python or open source tech with focus to deliver high Quality and accurate ML prediction Model
• Gather additional and external data sources to support the AI/ML Model as desired .
• Support the ML Model and FINE TUNEit to ensure high accuracy all the time.
• Example of use cases (Customer Segmentation , Product Recommendation, Price Optimization, Retail Customer Personalization Offers, Next Best Location for Business Est, CCTV Computer Vision, NLP and Voice Recognition Solutions)

Required technology expertise :

• Deep Knowledge & Understanding on MACHINE LEARNING ALGORITHMS (Supervised / Unsupervised Learning / Deep Learning Models)
• Hands on EXP for at least 5+ years with PYTHON and R STATISTICS PROGRAMMING Languages
• Strong Database Development knowledge using SQL and PL/SQL
• Must have EXP using Commercial Data Science Solution particularly DATAIKU and (Altryx, SAS, Azure ML, Google ML, Oracle ML is a plus)
• Strong hands on EXP with BIG DATA Solution Architecture and Optimization for AI/ML Workload.
• Data Analytics and BI Tools Hand on EXP particularly (Oracle OBIEE and Power BI)
• Have implemented and Developed at least 3 successful AI/ML Projects with tangible Business Outcomes In retail Focused Industry
• Have at least 5+ Years EXP in Retail Industry and Customer Focus Business.
• Ability to communicate with Business Owner & stakeholders to understand their current issues and provide MACHINE LEARNING Solution accordingly.

Qualifications

• Bachelor Degree or Master Degree in Data Science, Artificial Intelligent, Computer Science
• Certified as DATA SCIENTIST or MACHINE LEARNING Expert.

1. Develop User interfaces for Modern Rich Internet Applications with the latest Front End Technologies Perform product analysis and development tasks of increasingly complex nature which may require extensive research and analysis.
2. Writing tested and documented JavaScript, HTML and CSS
3. Make design and technical decisions for AngularJS projects.
4. Ensuring high performance