Description

About Fort Technologies Fort Technologies leverages advanced technology to bring property owners and builders together safely and efficiently. The company focuses on building scalable, data-driven solutions that improve planning, decision-making, and operational efficiency across real-world systems. Job Summary Fort Technologies is seeking a skilled Data Scientist with strong foundations in data science, operations research, and core engineering principles to design and scale intelligent data-driven solutions. This role focuses on building scalable machine learning systems, solving complex optimization problems, and developing advanced analytics platforms to support large-scale, real-world applications. Key Responsibilities Machine Learning & Optimization Design, develop, and scale machine learning and deep learning workloads to handle large and high-velocity datasets Apply techniques at the intersection of Operations Research, Machine Learning, and Deep Learning to solve complex business and logistics problems Implement auto-scaling ML pipelines and automate testing of critical algorithms Data Platforms & Analytics Contribute to the development of logistics and planning pipelines integrating big data, optimization techniques, and ML models Build and enhance data platforms for large-scale data mining and insight generation Develop geo-analytical models and advanced clustering algorithms Advanced Analytics & NLP Design and implement NLP-based applications for text and unstructured data analysis Apply statistical modeling and optimization algorithms to improve decision-making Work with diverse data types including structured, semi-structured, and time-series data Collaboration & Engineering Collaborate with cross-functional engineering and business teams to deliver scalable solutions Leverage cloud-native AI/ML services for model deployment and optimization Support visualization and reporting on big data infrastructure Required Qualifications Bachelor’s or Master’s degree in any discipline (UG/PG) 1–3 years of hands-on experience in Data Science, Machine Learning, or Advanced Analytics Strong understanding of statistical modeling, ML techniques, and optimization algorithms Experience building ML models for large-scale and high-velocity datasets Technical Skills Programming & Frameworks Python, R Machine Learning & Deep Learning (TensorFlow, Keras) Big Data & Storage Spark, Hadoop SQL, NoSQL, Graph, and Time-Series Databases Visualization & Reporting Tableau, Power BI, Zeppelin, and open-source visualization tools Advanced Technologies Operations Research tools and techniques Geo-analytics and clustering algorithms Cloud platforms: Azure, AWS, GCP Preferred Skills Experience with cloud-native AI/ML solutions Exposure to supply chain, logistics, or optimization-driven domains Hands-on experience with big data visualization at scale Behavioral Skills Strong analytical and problem-solving mindset Ability to translate business problems into mathematical and ML solutions Excellent collaboration and communication skills Engineering mindset with focus on scalability and reliability Key Skills Data Science • Machine Learning • Operations Research • Optimization • Big Data • Data Mining • NLP • Geo Analytics • SQL • Python • Cloud Computing • Data Visualization

Role and Responsibilities

• Key Responsibilities Machine Learning & Optimization Design, develop, and scale machine learning and deep learning workloads to handle large and high-velocity datasets Apply techniques at the intersection of Operations Research, Machine Learning, and Deep Learning to solve complex business and logistics problems Implement auto-scaling ML pipelines and automate testing of critical algorithms Data Platforms & Analytics Contribute to the development of logistics and planning pipelines integrating big data, optimization techniques, and ML models Build and enhance data platforms for large-scale data mining and insight generation Develop geo-analytical models and advanced clustering algorithms Advanced Analytics & NLP Design and implement NLP-based applications for text and unstructured data analysis Apply statistical modeling and optimization algorithms to improve decision-making Work with diverse data types including structured, semi-structured, and time-series data Collaboration & Engineering Collaborate with cross-functional engineering and business teams to deliver scalable solutions Leverage cloud-native AI/ML services for model deployment and optimization Support visualization and reporting on big data infrastructure