Data Scientist

About Docupath

Docupath is an AI SaaS company that helps teams manage and automate document processing with efficiency and accuracy. Operating at the intersection of Cognitive AI, large language models, and data extraction, our platform transforms unstructured business documents into highly accurate, machine-readable structured data, enabling enterprises across the globe to streamline workflows, improve compliance, and accelerate decision-making.

We are a fast-growing startup that values ownership, clarity, and operational excellence across every function. Our rapidly expanding team thrives on innovation, collaboration, and technical excellence.

Role Overview

We are looking for a Data Scientist who will support data-driven decision-making across the business by building reliable dashboards, analysing data patterns, and contributing to machine learning and AI initiatives. This is an early-career role suited to someone with strong analytical judgement, practical dashboarding experience, and excellent English communication skills.

Key Responsibilities

1. Analytics & Dashboarding

Build and maintain dashboards and reporting layers that give Product, Operations, Delivery, and leadership clear visibility into platform performance and customer outcomes.

• Design, build, and maintain dashboards using tools such as Tableau, Grafana, or Python-based technologies such as Dash, Streamlit, Plotly, or equivalent.
• Translate business questions into meaningful metrics, visualisations, and reporting views that support decision-making.
• Monitor product usage, processing quality, operational performance, and customer-related data to identify trends and risks.
• Improve reporting quality by identifying data gaps, inconsistencies, and opportunities for automation.

2. Data Analysis & Insight Generation

Apply a strong analytical eye to complex and sometimes messy data, producing insights that improve product quality, customer outcomes, and internal execution.

• Analyse structured and semi-structured data to identify trends, anomalies, correlations, and improvement opportunities.
• Work with product and operational teams to understand data context, define analysis questions, and interpret results accurately.
• Prepare clear written summaries, charts, and recommendations for internal stakeholders.
• Support experiment tracking, performance reviews, data quality checks, and recurring business reporting.

3. Machine Learning, AI & LLM Support

Contribute to machine learning and AI-related initiatives that improve Docupath’s document processing capabilities and customer-facing product experience.

• Support model evaluation, error analysis, and performance monitoring for AI and machine learning workflows.
• Apply a working understanding of machine learning concepts such as model validation, feature analysis, classification, and evaluation metrics.
• Assist with data preparation, testing, and feedback loops for AI-enabled product features.
• Contribute to LLM-based product exploration, including prompt evaluation, output quality assessment, and practical use-case analysis.

Note: Hands-on experience with LLMs, GenAI tools, or building products around AI/LLM capabilities is an advantage, but not mandatory for all candidates.

4. Product & Engineering Collaboration

Work closely with Product and Engineering to turn data requirements into practical, maintainable, and scalable solutions.

• Use Python and SQL to query, clean, analyse, and present data in a repeatable way.
• Collaborate with engineers to understand data pipelines, product events, APIs, and system behaviour relevant to analytics and reporting.
• Provide clear data requirements for new product features, dashboards, and internal tools.
• Contribute to lightweight internal tools, notebooks, scripts, or prototypes that improve team productivity.

Required Experience & Profile

• 3-5 years of experience as a Data Scientist, Associate Data Scientist, Analytics Engineer, BI Analyst, or equivalent analytical/data-focused role.
• Practical experience building dashboards and reports using Tableau, Grafana, or Python dashboarding technologies such as Dash, Streamlit, Plotly, or similar tools.
• Strong analytical ability with the judgement to identify patterns, question assumptions, and turn data into clear recommendations.
• Good working knowledge of Python for data analysis, including libraries such as pandas, NumPy, scikit-learn, or equivalent.
• Good working knowledge of SQL and comfort working with product, operational, and relational datasets.
• Understanding of core machine learning and AI concepts, including model evaluation and data preparation.
• Exposure to LLMs, GenAI tools, prompt testing, AI product features, or model output evaluation would be an advantage.
• Exposure to software development practices such as Git, APIs, testing, cloud services, or deployment workflows would be an advantage.
• Experience working with system integrations and automation platforms such as Zapier and Maxio is considered a plus. Familiarity with managing, troubleshooting, and optimizing third-party integrations across business systems will be beneficial for the role.
• Excellent English communication skills, both written and verbal.

Personal Attributes

• Analytical and curious, with a genuine interest in understanding how products, data, and AI systems behave in the real world.
• Detail-oriented, with the ability to spot data quality issues, inconsistencies, and unusual patterns.
• Pragmatic problem solver who focuses on useful outputs rather than over-engineered analysis.
• Clear communicator who can simplify technical findings for non-technical stakeholders.
• Collaborative, proactive, and comfortable working across Product, Engineering, Operations, and Delivery.

Who Should Apply?

This role suits professionals from backgrounds such as:

• Associate Data Scientists or early-career Data Scientists looking to work on applied AI and product analytics in a fast-growing technology company.
• BI Analysts, Data Analysts, or Analytics Engineers with strong dashboarding experience and an interest in machine learning and AI.
• Python-oriented analysts who have built dashboards, analytical tools, or reporting workflows and want to move closer to AI product development.
• Junior data professionals with strong communication skills, practical dashboarding capability, and a strong analytical mindset.

Why Join Docupath?

• Work on applied AI and data problems in a real enterprise document processing and AP automation platform.
• High exposure to Product, Engineering, Delivery, and Operations in a fast-growing AI-native company.
• Opportunity to shape dashboards, metrics, and analytical practices as the company scales.
• Hands-on role with room to grow into deeper data science, AI product, or analytics engineering responsibilities.
• Be part of a flat, innovation-driven culture that encourages ownership, creativity, and collaboration.
• Competitive salary, paid in USD, with strong opportunities for career growth.

Ready to build with us?

Apply now to recruitment@docupath.ai with your resume!