Data-Hat AI

Data-Hat AI is an enterprise AI solutions provider specializing in Generative AI and AI Agents. Their platform automates workflows, optimizes pricing, improves marketing effectiveness, minimizes returns, and enhances supply chain operations. Led by Kshitij Kumar (KK), a recognized Top 100 CDO, the company focuses on responsible AI, data privacy, and delivering measurable business outcomes for clients. They aim to redefine enterprise decision-making by empowering businesses with intelligent, human-like AI agents that understand, analyze, and act on data, transforming complexity into clarity and insight into impact. They serve various industries including e-commerce, manufacturing, supply chain, healthcare, finance, and real estate.

AI AgentsAutomationData MonetizationEnterprise AIGenerative AIPredictive AnalyticsProcess OptimizationResponsible AIdata-hat.com

Data-Hat AI

AI AgentsAutomationData MonetizationEnterprise AIGenerative AIPredictive AnalyticsProcess OptimizationResponsible AIdata-hat.com

HQUS

Team Size13

Open Jobs7

Total Funding-

Latest FundraiseUnknown

Join the Team

Experienced Machine Learning Engineer - Retail Focused

RemoteIN

Remote • IN

Teeming tracks opportunities at over 24,000 AI startups, then works with you to find (and land) the one you'll love.

Machine Learning Engineer

Part-timeAustin, US

Part-time • Austin, US

Data Scientist

Part-timeTel Aviv

Part-time • Tel Aviv

Product Designer

Part-timeUtrecht, NL

Part-time • Utrecht, NL

DevOps Engineer

ContractAmsterdam, NL

Contract • Amsterdam, NL

Software Engineer

InternshipAmsterdam, NL

Internship • Amsterdam, NL

Backend Developer

InternshipHamburg, DE

Internship • Hamburg, DE

Company Overview

At DataHat, we are a leading player in the retail industry, revolutionizing how we engage with customers, optimize supply chains, and drive business growth. We are seeking an experienced Machine Learning Engineer with a deep understanding of the retail sector to join our dynamic team. This is a unique opportunity to leverage cutting-edge machine learning techniques to deliver impactful solutions in a rapidly evolving industry.

Role Overview

As an Experienced Machine Learning Engineer specializing in Retail, you will be at the forefront of developing and implementing machine learning models that address real-world retail challenges. You will work on a range of projects, from customer personalization and demand forecasting to inventory optimization and pricing strategies. Your deep knowledge of retail operations combined with technical expertise will play a critical role in shaping the future of our products and services.

Key Responsibilities

Key Requirements

Preferred Qualifications

Education : Bachelor's or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
Retail-Specific Tools : Experience with retail-specific software and platforms (e.g., SAP, Oracle Retail, Salesforce, etc.).
Big Data Technologies : Familiarity with big data tools like Hadoop, Spark, and distributed computing frameworks.
Deep Learning : Experience with deep learning techniques and neural networks, especially for recommendation engines, NLP, and computer vision tasks.

What We Offer

Competitive salary and performance-based incentives.
Opportunity to work in a fast-paced, innovative environment.
Career growth and development opportunities within a rapidly growing company.
Collaborative and supportive team culture.

ML Model Development : Design, develop, and deploy machine learning models tailored to the retail sector (e.g., recommendation systems, customer segmentation, sales prediction, dynamic pricing, etc.).

Retail Domain Expertise : Utilize your deep understanding of retail operations, customer behavior, and market trends to craft innovative and data-driven solutions.

Data Strategy : Collaborate with data engineers and business stakeholders to source, preprocess, and integrate large datasets from various retail systems (e.g., POS, inventory, CRM, eCommerce platforms).

Cross-Functional Collaboration : Work closely with product managers, data scientists, and business teams to translate complex business problems into machine learning solutions.

Model Optimization : Continuously optimize models for performance, scalability, and business impact, leveraging tools like hyperparameter tuning and cross-validation.

Communication & Stakeholder Engagement : Present findings, insights, and recommendations to non-technical stakeholders in clear and actionable ways.

Research & Innovation : Stay ahead of industry trends and emerging technologies in machine learning, retail analytics, and AI, contributing to the evolution of our product offerings.

Experience : Minimum of 5+ years as a Machine Learning Engineer, Data Scientist, or similar role with a proven track record in the retail sector.

Domain Knowledge : In-depth understanding of retail operations, eCommerce, consumer behavior, inventory management, pricing, and demand forecasting.

Technical Skills :

Strong proficiency in Python and machine learning libraries (TensorFlow, PyTorch, Scikit-learn, etc.).

Solid experience with data processing, feature engineering, and data wrangling techniques.

Expertise in building and deploying machine learning models at scale.

Familiarity with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).

Strong understanding of algorithms, statistics, and optimization methods.

Excellent written and verbal communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.

Ability to present data-driven insights and recommendations in a compelling manner.

Collaboration : Strong team player with a collaborative mindset and the ability to work in cross-functional teams.

Problem-Solving : Demonstrated ability to solve complex, ambiguous problems and deliver impactful solutions in a fast-paced, dynamic environment.

Model Interpretability : Experience with model explainability tools (e.g., SHAP, LIME) and understanding of regulatory requirements in retail analytics.