Mandatory Skills:
Anyone-GCP/AWS/ Azure
Python, TensorFlow, PyTorch ML, SQL
Please find the below mandatory skills for this position:
We are looking for candidates with experience in the end-to-end machine learning application development lifecycle: training, evaluating, and deploying machine learning / deep learning models into production environments, with measurable business impact.They should have an in-depth understanding of machine learning / deep learning models and methods, and experience building Python-based applications to support model inference
Senior Data Scientist
Summary
We are seeking a highly motivated and experienced Senior Data Scientist to join our team. The ideal candidate will have a strong understanding of data science principles, a proven track record of deploying robust machine learning solutions, and a passion for leveraging data to drive decision-making. This role offers the opportunity to drive technical direction in an innovative and collaborative team environment working on a high-impact data product.
Key Responsibilities
Design and train predictive models, including deep learning models, to optimize key business outcomes and address complex challenges. Engineer impactful features and build robust, automated data pipelines to support model training and inference. Rigorously analyze model performance and systematically fine-tune models to maximize business metrics. Build and deploy scalable, low-latency, production-grade applications to serve models in a production cloud environment. Use a production-first mindset to consult on project feasibility and help shape technical strategy, balancing performance, time, and cost. Design and validate new processes, products, and advanced ML techniques through experimentation and testing. Analyze large structured and unstructured datasets to identify insights and propose strategies to address complex technical challenges. Communicate complex findings and strategic recommendations to technical and non-technical audiences concisely and effectively. Proactively engage with team members to accomplish individual and groups goals, providing technical mentorship to other data scientists. Continuously seek new opportunities to develop and apply new skills towards the improvement of data science processes and technical methodologies. Establish comprehensive monitoring for model performance and data drift, using insights to drive continuous improvement. Document complex model architectures, deployment processes, and data pipelines to ensure maintainability.
Critical Qualifications
Bachelor’s degree in a discipline such as Computer Science, Data Science, Engineering, Applied Math, or a related field. 5+ years of relevant work experience in a data science or machine learning role with demonstrated history of project ownership and delivery. Proven experience in designing, training, and deploying machine learning models into production environments with measurable impact. Extensive experience working in a cloud environment (GCP is preferred, but cloud skills are transferable). Expert proficiency in SQL and Python, with strong ability to write clean, efficient, and reusable code for both model training and application development. Expertise in a wide range of machine learning algorithms, statistical methods, and deep learning frameworks (e.g. scikit-learn, Keras, TensorFlow, PyTorch). Experience building Python-based applications to serve model predictions for online inference. Experience applying Natural Language Processing techniques to build solutions using unstructured data. Expertise with using Git in a collaborative team environment. Proven ability to perform statistical analysis to validate model performance and business impact. Strong communication and presentation skills, with the ability to convey complex technical concepts to both technical and non-technical audiences. Demonstrated experience in providing technical mentorship to other data scientists.
Preferred Qualifications
Master’s or Ph.D. in a discipline such as Computer Science, Data Science, Engineering, Applied Math, or a related field. Professional certification in cloud-based data platforms and services (e.g. GCP Professional Machine Learning Engineer). In-depth knowledge of ML Ops principles and familiarity with associated methods/tools. Demonstrated experience building ML models for matching, ranking, or recommendation systems.
