Data Scientist

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HubSpot

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2006

🤝 B2B

☁️ SaaS

B2B • SaaS • Marketing

HubSpot is an AI-powered customer platform that combines marketing, sales, and customer service software into one integrated suite. With over 238,000 customers in 135 countries, HubSpot offers tools for marketing automation, sales management, customer service, content marketing, operations, and B2B commerce. With products like Marketing Hub, Sales Hub, Service Hub, and Content Hub, HubSpot enables businesses to generate leads, close deals, and provide excellent customer support, all while using AI to enhance operations and insights. The platform is designed to unify teams and customer data, supporting both small startups and large enterprises in their growth journey.

📋 Description

• Develop and implement data models, analytics solutions, and reporting capabilities to support business objectives. • Analyse large and complex datasets to identify trends, patterns, and opportunities for improvement. • Build, test, and maintain statistical and machine learning models. • Support data integration and ETL processes, ensuring data quality and consistency across systems. • Collaborate with stakeholders to gather requirements and translate business needs into analytical solutions. • Create dashboards, reports, and visualisations that provide actionable insights. • Assist in the deployment, monitoring, and continuous improvement of data science solutions. • Identify opportunities to improve processes, data quality, and operational efficiency. • Work closely with engineering, product, and business teams to deliver high-quality solutions.

🎯 Requirements

• 3–5 years of experience in Data Science, Analytics, Machine Learning, or a related field. • Experience developing and implementing data models, analytical solutions, and machine learning algorithms. • Strong programming skills in Python and experience with data analysis tools and libraries. • Experience working with SQL and relational databases such as MySQL and PostgreSQL. • Understanding of ETL processes, data modelling, and data warehousing concepts. • Knowledge of machine learning techniques and statistical analysis methods. • Experience working with cloud-based data platforms and services. • Familiarity with big data technologies such as Apache Spark, Hadoop, Amazon EMR, or Kinesis is advantageous. • Experience using version control tools such as Git or Bitbucket. • Strong analytical and problem-solving skills with attention to detail. • Excellent communication skills and the ability to explain technical concepts to both technical and non-technical audiences. • Ability to work effectively in a collaborative and fast-paced environment.

🏖️ Benefits

• Professional development opportunities • Work across departments to gain new skills and valuable experience.