Job
Description
About Us: Traya is an Indian direct-to-consumer hair care brand platform provides a holistic treatment for consumers dealing with hairloss. The Company provides personalized consultations that help determine the root cause of hair fall among individuals, along with a range of hair care products that are curated from a combination of Ayurveda, Allopathy, and Nutrition. Traya's secret lies in the power of diagnosis. Our unique platform diagnoses the patient’s hair & health history, to identify the root cause behind hair fall and delivers customized hair kits to them right at their doorstep. We have a strong adherence system in place via medically-trained hair coaches and proprietary tech, where we guide the customer across their hair growth journey, and help them stay on track. Traya is founded by Saloni Anand, a techie-turned-marketeer and Altaf Saiyed, a Stanford Business School alumnus. Our Vision: Traya was created with a global vision to create awareness around hair loss, de-stigmatise it while empathizing with the customers that it has an emotional and psychological impact. Most importantly, to combine 3 different sciences (Ayurveda, Allopathy and Nutrition) to create the perfect holistic solution for hair loss patients. Responsibilities: Data Analysis and Exploration: Conduct in-depth analysis of large and complex datasets to identify trends, patterns, and anomalies. Perform exploratory data analysis (EDA) to understand data distributions, relationships, and quality. Machine Learning and Statistical Modeling: Develop and implement machine learning models (e.g., regression, classification, clustering, time series analysis) to solve business problems. Evaluate and optimize model performance using appropriate metrics and techniques. Apply statistical methods to design and analyze experiments and A/B tests. Implement and maintain models in production environments. Data Engineering and Infrastructure: Collaborate with data engineers to ensure data quality and accessibility. Contribute to the development and maintenance of data pipelines and infrastructure. Work with cloud platforms (e.g., AWS, GCP, Azure) and big data technologies (e.g., Spark, Hadoop). Communication and Collaboration: Effectively communicate technical findings and recommendations to both technical and non-technical audiences. Collaborate with product managers, engineers, and other stakeholders to define and prioritize projects. Document code, models, and processes for reproducibility and knowledge sharing. Present findings to leadership. Research and Development: Stay up-to-date with the latest advancements in data science and machine learning. Explore and evaluate new tools and techniques to improve data science capabilities. Contribute to internal research projects. Qualifications: Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, or a related field. 3-5 years of experience as a Data Scientist or in a similar role. Leverage SageMaker's features, including SageMaker Studio, Autopilot, Experiments, Pipelines, and Inference, to optimize model development and deployment workflows. Proficiency in Python and relevant libraries (e.g., scikit-learn, pandas, NumPy, TensorFlow, PyTorch). Solid understanding of statistical concepts and machine learning algorithms. Excellent problem-solving and analytical skills. Strong communication and collaboration skills. Experience deploying models to production. Experience with version control (Git) Preferred Qualifications: Experience with specific industry domains (e.g., e-commerce, finance, healthcare). Experience with natural language processing (NLP) or computer vision. Experience with building recommendation engines. Experience with time series forecasting. Show more Show less
