About the Role :

Arrive is seeking a Senior Data Scientist with a strong technical background to join our growing Data Science team in the AI & Analytics Experience. The purpose of this role is to deliver data science products and impactful solutions across the organization, playing a key role in advancing Arrive's data capabilities and ensuring data insights are effectively integrated into decision-making.

How To Make An Impact :

- Lead the end-to-end lifecycle of ML projects - from problem framing, data exploration, feature engineering, and model development to deployment and monitoring.

- Partner with cross-functional leadership on joint strategic initiatives to deliver measurable business impact.

- Identify, address, and resolve architectural and technical hurdles in developing scalable data science solutions.

- Drive architectural decisions regarding pipelines, model registries, or feature store development ensuring scalability, cost efficiency and reliability.

- Raise the technical bar of the team by actively mentoring other data scientists and promoting engineering best practices.

- Stay curious by exploring and implementing cutting-edge data science technologies to foster continuous team innovation.

- Translate complex data insights into practical business strategies and lead technical discussions with senior stakeholders.

- Mentoring junior data scientists and partnering with other DNA leads to nurture a data-driven culture and improve data literacy throughout Arrive.

- Design and prototype Generative AI solutions using LLMs, RAG (Retrieval-Augmented Generation), embeddings, vector databases, prompt engineering, and fine-tuning (LoRA/PEFT).

Your Background :

- At least 5 years of experience working as a Data Scientist, with a proven track record of leading multi-month projects with measurable business impact.

- Strong command of classical ML techniques - regression, classification, ensemble methods, clustering, dimensionality reduction, time-series forecasting, causal inference and optimization techniques.

- Strong expertise in Python and data science libraries, along with deep proficiency in SQL and cloud architectures and services (e.g., AWS SageMaker, S3, Lambda, ECR or Snowflake or Airflow).

- Proven experience mentoring other data scientists, raising technical standards, and advocating for software development best practices.

- Demonstrated ability to drive architectural decisions (such as pipelines, model registries, or feature stores) and represent data science at a senior stakeholder level.

- Solid software engineering foundations or an advanced degree (Masters/PhD) in a relevant field (e.g., machine learning or mobility).

- Experience with geospatial data (e.g., GeoPandas) or big data tools (e.g., PySpark) is highly preferred.

- Hands-on experience with MLOps - model deployment, CI/CD pipelines, monitoring, experiment tracking and containerization (Docker, Kubernetes).

- Practical experience with Generative AI / LLMs - prompt engineering, RAG pipelines, embeddings, fine-tuning, and evaluation frameworks for GenAI systems.

- Excellent communication skills, with the ability to translate technical concepts for business stakeholders in English.

- This role is based in Bengaluru, India.