Data Scientist / Data Analyst - AI

Position Overview

We are seeking a skilled and motivated Data Scientist / Data Analyst with expertise in AI and Machine Learning to join our data-driven team. This role involves analyzing complex data sets, deriving actionable insights, building predictive models, and applying artificial intelligence to solve real-world problems. The ideal candidate will have strong analytical and coding skills, a solid understanding of statistical and machine learning techniques, and a curiosity-driven mindset. This position bridges the gap between raw data and strategic decision-making using AI tools, statistical techniques, and domain knowledge to optimize business processes, predict outcomes, and create intelligent solutions.

Key Responsibilities

1. Data Collection, Cleaning, and Preparation

• Collect, extract, and transform large structured and unstructured datasets from various sources (databases, APIs, Excel, CSV, etc.).
• Clean, filter, and preprocess data to ensure high quality and integrity.
• Perform feature engineering and selection to enhance model performance.

2. Data Analysis and Business Insights

• Analyze data trends, patterns, and correlations using statistical tools and techniques.
• Use exploratory data analysis (EDA) to summarize and visualize datasets.
• Deliver insights and data-driven recommendations to stakeholders through dashboards, charts, and written reports.
• Work with business teams to identify KPIs and build performance-tracking systems.

3. Machine Learning and AI Model Development

• Design and build predictive and classification models using algorithms like linear regression, decision trees, random forests, SVM, XGBoost, clustering (K-Means, DBSCAN), and deep learning.
• Train, validate, and test AI/ML models with performance metrics such as accuracy, F1-score, recall, and AUC.
• Use advanced AI techniques such as NLP (Natural Language Processing), image processing, or time-series forecasting as applicable.
• Deploy models into production using APIs, containers, or cloud platforms (AWS, Azure, GCP).

4. Data Visualization and Reporting

• Develop dashboards and real-time reports using tools such as Power BI, Tableau, or Plotly/Dash.
• Create compelling data stories that simplify complex concepts for non-technical stakeholders.
• Automate reporting processes and standardize KPIs across teams.

5. Collaboration and Cross-functional Work

• Collaborate with product managers, engineers, and business analysts to define data requirements and implement AI-driven features.
• Work closely with DevOps and IT teams to ensure secure and scalable data pipelines and deployments.
• Communicate model outputs and implications clearly to stakeholders in different departments.

6. Research and Innovation

• Stay updated with the latest trends, tools, and methodologies in AI, ML, and data science.
• Participate in data science workshops, hackathons, or internal innovation labs.
• Propose experimental AI solutions to optimize internal operations or improve customer experience.

Required Qualifications and Skills

Educational Background:

• Bachelor s or Master s degree in Computer Science, Statistics, Data Science, Engineering, Mathematics, or a related field.