AI Developer

Data Analysis & Insights Generation (30%)

• Perform exploratory data analysis (EDA) and statistical profiling using Python (leveraging libraries such as Pandas, NumPy, and SciPy) and Java for backend data processing tasks.
• Develop reusable scripts and modular code for data wrangling, anomaly detection, and KPI tracking.
• Apply object-oriented programming principles to build scalable data pipelines and analytical utilities.

Data Visualization & Reporting (40%)

• Design and implement interactive dashboards using Tableau, Power BI, or custom-built web interfaces.
• Utilize DAX, Power Query, and Salesforce APIs to integrate disparate data sources into unified reporting layers.
• Translate complex datasets into intuitive visual narratives that support executive decision-making.

Data Extraction & Preparation (40%)

• Build and maintain ETL workflows using Python, Java, and SQL-based tools to extract data from PostgreSQL, MSSQL, and cloud-based data lakes.
• Automate data cleansing and transformation routines using Apache POI (for Excel automation in Java), VBA, and Power Query.
• Ensure data integrity through rigorous validation, schema enforcement, and exception handling.

REQUIREMENTS

• Programming Proficiency: Strong command of Python for data analysis and scripting, and working knowledge of Java for backend data processing and integration tasks.
• SQL Expertise: Advanced querying skills across relational databases (PostgreSQL, MSSQL).
• Data Engineering Mindset: Familiarity with ETL concepts, data modeling, and pipeline orchestration.
• Tool Agnostic Flexibility: Comfortable switching between tools and languages to solve problems efficiently.
• Collaborative Communication: Ability to work closely with data scientists, business stakeholders, and technical teams to translate requirements into analytical solutions.

NICE TO HAVES (Or Things You’ll Get To Learn)

• Experience with DuckDB, Polars, or other high-performance analytical engines.
• Exposure to cloud data platforms like AWS Redshift, Azure Synapse, or Google BigQuery.
• Familiarity with Git for version control and collaborative development.
• Interest in machine learning, predictive modeling, or statistical inference.
• Prior experience in financial services or other regulated industries.

QUALIFICATIONS

• 2+ years of experience in data analysis, software development, or business intelligence, preferably in financial services or a regulated industry.
• Proficiency in Python and Java, with experience in data manipulation, automation, and backend integration.
• Strong SQL skills and familiarity with relational databases (PostgreSQL, MSSQL).
• Experience with data visualization tools (Power BI, Tableau) and dashboard development.
• Familiarity with ETL processes, data modeling, and version control systems (e.g., Git).
• Experience with Excel (including Power Query and VBA), and process documentation tools (Visio, Lucidchart).
• Excellent communication and stakeholder management skills.
• Bachelor’s degree in Computer Science, Data Science, Information Systems, or a related field.
• High proficiency in technical writing and documentation