Senior Data Scientist

As a Senior Data Scientist, you will leverage cutting-edge technologies and methodologies to deliver data-driven insights and solutions for complex customer needs. You will work on end-to-end solutions, including building Proof of Concepts (POCs), professional services, and integrating third-party technologies with client systems. This role is pivotal to ensuring the successful implementation of data science-driven products and capabilities, with a key focus on AI, machine learning, and Natural Language Processing (NLP). You will collaborate closely with cross-functional teams, delivering innovative solutions to customers in highly dynamic, data-intensive environments.

• Lead and execute complex customer engagements, utilizing specialized expertise in AI, Machine Learning, and NLP, including building POCs, integrations, and deployments with customer workflows.
• Apply a combination of technical, product, and data science expertise to co-create solutions that address specific customer needs, including ideation, clarification, technical design, and documentation.
• Lead detailed customer presentations for complex technical propositions, focusing on explaining advanced data science concepts and AI/ML solutions in an accessible way.
• Manage relationships with internal and external stakeholders, ensuring that project and customer-specific technical requirements are captured, refined, and translated into actionable solutions.
• Oversee and contribute to the development of Proof of Concepts, ensuring integration with customer workflows and systems.
• Lead the technical design and implementation of AI and machine learning solutions that integrate with existing client infrastructure.
• Drive the adoption of advanced data science and AI technologies to deliver high-value solutions.
• Develop and present strategies for scaling AI solutions, utilizing cloud platforms (Azure, AWS, GCP) for production-ready deployments.
• Lead and mentor junior team members, fostering a collaborative environment for continuous learning and technical growth.

• 10+ years of experience in data science or a related field, with a focus on AI, machine learning, and NLP, preferably in a senior technical or leadership role.
• Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field. A Ph.D. in a relevant field is a plus.
• Expertise in Natural Language Processing (NLP) with a deep understanding of the latest NLP stack, including transformer-based architectures such as BERT, GPT, T5, and newer models like GPT-4, PaLM, and other state-of-the-art large language models (LLMs) that are driving the evolution of NLP applications.
• Extensive experience with advanced machine learning and deep learning frameworks such as TensorFlow 2.x, PyTorch, Hugging Face, and JAX for NLP and other advanced AI tasks.
• Deep knowledge of cloud services (AWS, GCP, Azure) and their use in data science workflows, particularly for deploying machine learning models at scale.
• Expertise in Python, with advanced knowledge of modern data science and machine learning libraries such as Pandas, NumPy, SciPy, scikit-learn, spaCy, as well as cutting-edge NLP frameworks like Hugging Face Transformers, Datasets, and NLTK for efficient model training, fine-tuning, and data preprocessing.
• Strong programming skills in Python, R, and SQL, with advanced proficiency in handling large-scale data using distributed data systems like Apache Spark, cloud-native NoSQL databases such as MongoDB, Cassandra, and DynamoDB, as well as search engines like Elasticsearch and vector databases for semantic search (e.g., Pinecone, Weaviate).
• Hands-on experience with data ingestion, data wrangling, and data pipeline orchestration using tools like Apache Kafka, Apache Spark, Airflow, and distributed computing frameworks like Dask and Ray.
• Experience with advanced data science methodologies, including ensemble learning, deep reinforcement learning, transfer learning, and deploying large pre-trained models for real-time inference and production.
• Ability to design, prototype, and deploy NLP models for a range of applications, from information retrieval to sentiment analysis, chatbots, and question answering systems.
• Demonstrated success in delivering solutions in complex, fast-paced environments with a focus on customer satisfaction and technical excellence.
• Strong communication skills, with the ability to explain complex technical concepts to both technical and non-technical stakeholders.
• Proven experience in customer-facing roles is highly valued, particularly in the enterprise tech or financial sectors.
• Familiarity with AI-powered product development in industries such as finance, healthcare, or e-commerce.
• Experience with data visualization tools like Tableau, Power BI, or Plotly to present data science findings effectively.
• Knowledge of regulatory requirements in finance, including experience working with financial data feeds and APIs.