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Arrive

Global urban mobility platform with payments

Senior Data Scientist

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listedIn-person

About the Job

Requirements

  • 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 machine-learning techniques, including 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 such as AWS SageMaker, S3, Lambda, ECR, 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 (Master's or PhD) in a relevant field, such as machine learning or mobility.
  • Hands-on experience with MLOps, including model deployment, CI/CD pipelines, monitoring, experiment tracking, and containerization with Docker or Kubernetes.
  • Practical experience with Generative AI and large language models, including prompt engineering, retrieval-augmented generation pipelines, embeddings, fine-tuning, and evaluation frameworks for Generative AI systems.
  • Excellent communication skills, with the ability to translate technical concepts for business stakeholders in English.

Responsibilities

  • Lead the end-to-end lifecycle of machine-learning 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.
  • Mentor other data scientists and promote engineering best practices to raise the team's technical standards.
  • Explore and implement data science technologies to foster continuous team innovation.
  • Translate complex data insights into practical business strategies and lead technical discussions with senior stakeholders.
  • Mentor junior data scientists and partner with other DNA leads to nurture a data-driven culture and improve data literacy throughout Arrive.
  • Design and prototype Generative AI solutions using large language models, retrieval-augmented generation, embeddings, vector databases, prompt engineering, and fine-tuning with LoRA/PEFT.

Desired Qualifications

  • Experience with geospatial data, such as GeoPandas, or big data tools, such as PySpark, is highly preferred.

About the Company

Arrive

Global urban mobility platform with payments

Arrive is a global urban mobility platform formed by the merger of EasyPark Group and Flowbird Group. It offers smart payment systems for parking, public transit, and electric vehicle charging, plus data-driven tools to reduce traffic and optimize parking. It works by deploying scalable infrastructure so people can locate and pay for parking and transit on one platform, while partners manage mobility services and gain insights from data. Its goal is to improve urban life by making mobility more efficient and livable at a city-wide and business scale.

Company size
51-200
Company stage
Early VC
Total funding
$56.2M
Headquarters
Chicago, IL
Founded
2006

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