Data Scientist II

Data Scientist II

About Us:

6sense is a Predictive Intelligence Engine that is reimagining how B2B companies do sales and marketing. It uses big data at scale, advanced machine learning and predictive modelling to find buyers and predict what they will purchase, when and how much.

6sense helps B2B marketing and sales organizations fully understand the complex ABM buyer journey. By combining intent signals from every channel with the industry’s most advanced AI predictive capabilities, it is finally possible to predict account demand and optimize demand generation in an ABM world. Equipped with the power of AI and the 6sense Demand PlatformTM, marketing and sales professionals can uncover, prioritize, and engage buyers to drive more revenue.

We’ve more than doubled our revenue in the past five years and completed our Series E funding of $200M last year, giving us a stable foundation for growth.

Recent articles:

https://www.businesswire.com/news/home/20230815281505/en/6sense-Ranks-Number-763-on-The-Inc.-5000-the-Annual-Ranking-of-the-Fastest-Growing-Companies-in-America

https://martechseries.com/predictive-ai/ai-platforms-machine-learning/6sense-continues-to-lead-the-way-in-b2b-marketing-and-sales-with-seventh-consecutive-g2-leader-recognition/

https://www.businesswire.com/news/home/20230809060528/en/6sense-Named-to-the-2023-Forbes-Cloud-100

Purpose of the Job:

Data Scientist II leverages analytical and modelling skills to derive actionable insights from data, develop and evaluate models, and deploy AI solutions. The role focuses on fostering innovation, ensuring ethical data handling, and aligning with the product vision, ultimately contributing to data-driven decision-making, and enhancing stakeholder engagement. Effective collaboration within the team is vital for achieving these objectives.

Responsibilities & Accountabilities:

Understand AI concepts and apply them to solve business problems, identifying key stakeholders and relevant data sources. Evaluate and select basic algorithms and data sets for AI solutions, following established development practices and procedures.

Demonstrate strong proficiency in SQL and data manipulation tools, effectively working with larger and complex data sets.Apply statistical methods, machine learning algorithms, and data visualization techniques to

perform exploratory data analysis and derive key insights.

Build models using statistical software like R or Python and interpret existing models by experienced data scientists.

Apply data pre-processing techniques and utilize data visualization to interpret and communicate model outputs effectively.

Write well-documented, clean code with appropriate comments, adhering to best practices, and execute and document comprehensive test cases for AI modules and pipelines.

Apply data science concepts to align with product development, considering user needs and effectively communicating insights to stakeholders.

Recognize areas of improvement in existing data solutions, seek guidance, and contribute to new ideas through active participation in discussions.

Adhere to ethical guidelines and comply with industry standards in data handling and privacy.

Collaborate effectively within a team, understand stakeholder goals, and engage in productive communication, aligning with project and product objectives.

Evaluate existing models and suggest enhancements for better performance.

Integrate AI models into applications and workflows, ensuring effective deployment.

Educational and Experience Requirements:

Bachelor's or Master's degree in Data Science, Computer Science, Statistics, Mathematics, or a related field.

Minimum of 2 years of hands-on experience in data analysis, modeling, and AI solutions development.

Proficiency in handling and analyzing large, complex datasets using SQL and data manipulation tools.

Demonstrated expertise in implementing machine learning models and algorithms,

including regression, classification, and other advanced techniques.Strong programming skills in Python or R, showcasing the ability to write efficient, well- documented code.

Experience in utilizing data visualization techniques to interpret model outputs and communicate insights effectively.

Deploy AI solutions, integrate models into applications, and understand cloud platforms for deployment.

Proven ability to collaborate within a team, effectively communicate insights to stakeholders and work cohesively in a professional setting.

Demonstrated willingness to learn, adapt to new technologies and methodologies, and contribute to innovative ideas and approaches.

Adherence to ethical guidelines and best practices in data handling and privacy compliance.

Understanding of integrating data science concepts into product development and considering user needs for product enhancement.

Ability to analyze problems, make data-driven decisions, and optimize solutions to address business challenges.