Lead Data Scientist

1 month ago


bangalore, India Toplyne Full time
What is Toplyne?
Toplyne is the data scientist for Sales and Marketing teams. You can predict anything with Toplyne - New customers, expansion sales, cross-sells, imminent churn from inbound demand, and existing customers.
Toplyne lets you combine first-party data (product usage, CRM, data warehouse) and third-party intent to build machine learning models on demand, without code to identify high-propensity accounts.
About the role
Explore the hidden world of B2B SaaS but at a B2C scale. Work with trillions of clickstream events, 10s of millions of users, and a few unassuming terabytes of data.
As the Lead Data Scientist, you will play a pivotal role in driving our data science initiatives forward, work as an individual contributor while mentoring less experienced team members, and collaborate closely with cross-functional teams to deliver high-impact solutions. You will be responsible for overseeing the end-to-end development and deployment of models, while also championing best practices in MLOps.
Additionally, your role will involve:
Utilizing Python and Snowflake/SQL to extract, transform, and analyze large volumes of structured and unstructured data. Build robust data pipelines for data science workflows.
Implement best practices in MLOps, including version control, model tracking, and deployment automation using tools like MLFlow, DVC, and Airflow.
Develop scalable and reusable codebase for model development, evaluation, and monitoring.
Conduct thorough analysis and experimentation to improve model performance and accuracy.
Develop and deploy state-of-the-art classification models that drive business value. Hands-on experience on ensemble methods and deep learning techniques.
Collaborate with stakeholders (Data Engineers, Product Managers, Customer Success & SWEs) to define project requirements, scope, and success criteria.
Mentor junior data scientists and provide guidance on technical and methodological aspects of data science projects.
Stay up-to-date with the latest advancements in machine learning techniques and technologies, and evaluate their applicability to our business problems.
Ideal fit is?
We're looking for someone who:
Bachelor's degree or higher in Computer Science, Statistics, Mathematics, or a related field.
Proven experience (5+ years) in developing and deploying machine learning models.
Strong proficiency in Python programming and familiarity with libraries such as Pandas, NumPy, scikit-learn, etc.
Extensive experience with data engineering tools and technologies, including Airflow and Snowflake/SQL.
Hands-on experience with MLOps tools such as MLFlow, DVC, and Airflow.
Solid understanding of software development practices, including version control, code review, and testing.
Excellent problem-solving skills and ability to thrive in a fast-paced, collaborative environment.
Strong communication skills, with the ability to effectively articulate technical concepts to non-technical stakeholders.
Experience in leading and mentoring a team of data scientists is highly desirable.
‍ Interview Process?
We are a tight-knit team, and it's vital that we all get to know one another before diving in. We aim to ensure that you will thrive in your role within our team. Each conversation (via video conference) will last about 60 minutes, and the entire process typically spans 2 - 10 business days, across 4 rounds depending on everyone's schedules. Questions are always welcome
Read more about our people and culture here -
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