Data Scientist II - Finance Data Science

• Own end-to-end scalable machine learning models for risk assessment, forecasting, anomaly detection, customer clustering, natural language processing and other key finance initiatives.
• Apply large language models (LLMs) to create Gen-AI applications leveraging such as chatbots and intelligent agents to support & streamline finance operations.
• Partner with the strategic finance teams to enhance their financial forecasting methods and support data-driven decision-making.
• Analyze complex datasets of structured & unstructured data using advanced analytics to generate actionable insights; communicate findings through impactful reports and presentations.
• Establish best practices for data science, opportunity to mentor junior analysts and contribute to the team’s professional growth.
• Collaborate with stakeholders, data scientists and MLEs across various business groups to develop impactful solutions., HubSpot may use AI to help screen or assess candidates, but all hiring decisions are always human. More information can be found here. By submitting your application, you agree that HubSpot may collect your personal data for recruiting, global organization planning, and related purposes. We may use CLEAR ID Verification during the hiring process to confirm your identity and help maintain a safe, secure, and trusted experience for all candidates. Refer to HubSpot’s Recruiting Privacy Notice for details on data processing and your rights.

HubSpot, a market leader in sales and marketing technology, is the preferred platform for scaling businesses. Our Finance Data Science team drives innovation in data technologies to optimize business opportunities. We are expanding our team and seeking an experienced Senior Data Scientist to make a significant impact.

As a Senior Data Scientist on the newly formed Finance data science team, you’ll tackle key business challenges using data science, machine learning and Gen-AI solutions. This role is ideal for someone who enjoys solving complex data problems and collaborating with stakeholders and fellow data scientists. Strong coding skills in Python and SQL for data analysis, statistical modeling, ML and automation are essential. Experience with Large Language Models (LLMs) is a strong plus and any Java experience is nice to have., * Bachelor’s degree in Data Science, Computer Science, Statistics, Operations Research, or related field required. Masters preferred.

• 4+ years of experience as a Data Scientist or ML Engineer in a fast-paced environment owning end-to-end model lifecycle.
• Demonstrated experience in solving time series forecasting problems using a variety of techniques, along with delivering a broad range of other ML/AI solutions to address diverse business challenges.
• Expert-level proficiency in Python, with hands-on experience using key libraries such as Pandas, NumPy, SciPy, scikit-learn & popular nlp libraries along with strong expertise in version control tools like Git.
• Skilled in ML model monitoring, including tracking performance, detecting drifts and ensuring continuous improvement post-deployment.
• Experience leveraging large language models (LLMs) and experience with retrieval-augmented generation (RAG) concepts.
• Strong proficiency in SQL for data extraction and transformation.
• Ability to clearly communicate complex technical concepts to business leaders through presentations and written memos.
• Experience leading complex projects and collaborating across functional teams.

What Sets You Apart

• Experience with generative AI applications such as chatbots or autonomous agents.
• Proficiency in Java is a HUGE plus!
• Experience working with REST APIs to ingest and transform data into S3 buckets.
• Knowledge of MLOps for managing the ML lifecycle, with experience in cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes) is nice to have.
• Familiarity with FP&A metrics, SAAS economics and finance concepts.

The cash compensation below includes base salary, on-target commission for employees in eligible roles, and annual bonus targets under HubSpot’s bonus plan for eligible roles. In addition to cash compensation, some roles are eligible to participate in HubSpot’s equity plan to receive restricted stock units (RSUs). Some roles may also be eligible for overtime pay. Individual compensation packages are tailored to your skills, experience, qualifications, and other job-related reasons.

This resource will help guide how we recommend thinking about the range you see. Learn more about HubSpot’s compensation philosophy.

Benefits are also an important piece of your total compensation package. Explore the benefits and perks HubSpot offers to help employees grow better.

At HubSpot, fair compensation practices aren’t just about checking off the box for legal compliance. It’s about living out our value of transparency with our employees, candidates, and community. Annual Cash Compensation Range: $153,800-$246,100 USD

At HubSpot, we value both flexibility and connection. Whether you’re a Remote employee or work from the Office, we want you to start your journey here by building strong connections with your team and peers. If you are joining our Engineering team, you will be required to attend a regional HubSpot office for in-person onboarding. If you join our broader Product team, you’ll also attend other in-person events, such as your Product Group Summit and other gatherings, to continue building on those connections., HubSpot (NYSE: HUBS) is an AI-powered customer platform with all the software, integrations, and resources customers need to connect marketing, sales, and service. HubSpot’s connected platform enables businesses to grow faster by focusing on what matters most: customers.

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