Bridgehorn - Data Scientist - Data Analytics & Embedded AI Solutions (2-5 yrs)

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 work with a wide range of data-driven projects/initiatives, leveraging your expertise across various industries like Healthcare, Retail/CPG, Technology, Services etc. You will be responsible for developing and deploying AI/ML models, including latest advancements in Gen AI to solve business problems, improve customer experience, and optimize operations. You will collaborate with cross functional teams, providing data-driven insights and fostering a culture of data science excellence.

LOCATION: Hyderabad, India

RESPONSIBILITIES:

- Data Analysis & Modeling: Apply traditional and cutting-edge AI/ML techniques to analyse large datasets and build predictive, prescriptive, and generative models across multiple industries including healthcare, retail, CPG, and technology services.

- Advanced Machine Learning & AI Technologies: Leverage state-of-the-art machine learning (ML), deep learning (DL), and Generative AI (Gen AI) techniques, including GPT models, reinforcement learning, transfer learning, and others, to develop innovative solutions.

- Industry-Specific Insights: Utilize domain knowledge and sector expertise (e.g., healthcare data analytics, consumer behaviour analysis, and IoT) to generate meaningful insights and strategies that align with industry needs.

- Data Pipeline Development: Design and build robust, scalable data pipelines for data cleaning, preprocessing, and feature engineering. Work with both structured and unstructured data sources.

- Collaboration & Communication: Work closely with business stakeholders, product managers, and engineering teams to understand business requirements, translate them into data science solutions, and ensure effective model deployment.

- Generative AI Solutions: Experiment with and implement generative models, natural language processing (NLP), and creative AI solutions for diverse applications, such as content generation, personalization, and optimization.

- Continuous Learning & Innovation: Stay abreast of emerging AI/ML technologies and trends, especially in Gen AI, to push the boundaries of what's possible and maintain the company's competitive edge.

- Reporting & Visualization: Present analytical findings and model results to both technical and non-technical audiences using clear, visual storytelling. Develop interactive dashboards and visualizations to communicate complex insights.

EDUCATIONAL 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.

EXPERIENCE:

- Minimum of 5 years of experience in data science, with exposure to Healthcare, Retail/CPG, and Technology & Services industries.

- Proven track record of using traditional and advanced AI/ML models, including experience in Gen AI (e.g., GPT models, GANs, etc.).

- Experience with building end-to-end data science pipelines and deploying machine learning models to production

- Experience with Gen AI model development in real-world applications (e.g., text generation, image synthesis etc.)

- Familiarity with Agile methodologies and DevOps practices for data science projects/initiatives

PROGRAMMING SKILLS

- Excellent skills in SQL, Python & R are essential for this role

- Proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and data processing tools (e.g., Pandas, NumPy)

- Expertise in deep learning techniques and neural networks

- Familiarity with NLP, computer vision, and Gen AI applications

- Strong understanding of cloud-based platforms like Azure, AWS, GCP is a mandatory requirement for model development, testing and deployment in optimized environments.