Data Scientist - Analytics
First seen by Alion on Aug 24, 2026.
About Us
At Bridgehorn, we drive data-driven transformations by leveraging AI/ML, advanced analytics, and robust data management to enhance operational efficiency and help businesses achieve their goals. Our mission is to consistently innovate and deliver exceptional data and AI solutions that create value and drive client success.
As a rapidly growing company, we are seeking passionate professionals who share our ambitions and values. Join us across various roles and become a key part of our exciting growth journey.
Job Summary
As a Data Scientist at Bridgehorn, you will design, build, and deploy production machine learning systems that directly impact client operations. You will own the full ML lifecycle - from problem definition and model development to pipeline engineering and production deployment. Working in a client-facing capacity, you will translate business requirements into scalable ML solutions, including predictive models and GenAI orchestration systems. This role requires both deep technical capability and the ability to operate independently in ambiguous, greenfield environments.
Responsibilities
- Design and develop predictive models and machine learning pipelines for client deployment
- Build and orchestrate GenAI solutions including prompt engineering, RAG systems, and LLM integration
- Engineer production ML systems including data pipelines, model serving infrastructure, and monitoring frameworks
- Translate client business problems into technical ML solutions with minimal supervision
- Deploy models to production environments and ensure system reliability and performance
- Collaborate with engineering teams to integrate ML systems into client applications
- Build ML infrastructure and tooling from foundational components where existing systems are insufficient
- Communicate technical approaches and results to both technical and non-technical stakeholders
- Maintain model performance through monitoring, retraining, and iterative improvement
Qualifications
- Minimum B.Tech or equivalent degree in Computer Science, Statistics, or related field.
- MS in Business Analytics, Computer Science or related disciplines is preferred.
- Minimum of 2 years of experience in data science building and deploying ML models in production environments
- Strong programming skills in Python with experience in ML frameworks (scikit-learn, TensorFlow, PyTorch, XGBoost)
- Experience building data pipelines and ML infrastructure (Airflow, Kubernetes, Docker, cloud platforms)
- Hands-on experience with GenAI technologies including LLMs, prompt engineering, vector databases, and orchestration frameworks (LangChain, LlamaIndex)
- Proficiency in SQL and database systems
- Experience with MLOps practices including versioning, monitoring, and CI/CD for ML systems
- Ability to work independently on ambiguous problems with minimal guidance
- Strong communication skills for client-facing technical discussions
Programming Skills
- Excellent skills in SQL, Python & R
- Predictive modeling and statistical learning
- Familiarity with NLP, computer vision, and Gen AI applications
- Deep learning and neural network architectures
- GenAI orchestration and LLM integration
- Strong understanding of cloud-based platforms like Azure, AWS, GCP is a mandatory requirement for model development, testing and deployment in optimized environments.
Benefits
- Competitive salary and performance bonuses.
- Opportunities for continuous learning, professional development and certifications.
- Collaborative & inclusive work environment with a focus on innovation.
- Direct access to decision makers in the industry
Skills
NLP, Data Science, Data Scientist, Machine Learning, Data Management, Statistics, Analytics, Python, SQL