HCL AppScan is a comprehensive solution for application security testing and management activities that integrate directly into customers’ software development lifecycle. AppScan offers DAST, SAST, and IAST scanning technologies with greater accuracy and provides expanded testing and compliance reporting capabilities.

We are establishing a new initiative focused on leveraging Machine Learning and GenAI/LLM tools and techniques, as well as decades’ worth of relevant data, to drive innovation in R&D, Customer Success and Marketing/Sales.

We are looking for a talented and driven Lead Data Scientist to spearhead this effort.

Position Overview:

As the Lead Data Scientist, you will be responsible for initiating, developing and implementing ML and AI solutions that address complex business challenges. You will play a critical role in shaping our data science strategy, leading projects from conception to deployment, and mentoring other team members as the team grows. You will have the opportunity to define the technical direction of our AI/ML initiatives and directly impact the success of our organization.

Responsibilities:

• Lead the development and implementation of Machine Learning and Artificial Intelligence solutions.
• Identify business problems and translate them into data science projects.
• Research, evaluate, and select appropriate AI/ML models and algorithms.
• Develop and maintain data pipelines for data ingestion, cleaning, and processing.
• Train, evaluate, and deploy machine learning models in production environments.
• Monitor and maintain model performance, and iterate on models as needed.
• Stay current with the latest advancements in ML and AI, and propose innovative solutions.
• Mentor and guide junior data scientists or analysts as the team expands.
• Communicate findings and insights to technical and non-technical stakeholders.
• Define and manage project timelines and resources.

Requirements:

• 4+ years of experience in Data Science or Machine Learning roles, including ownership of end-to-end projects
• BSc in a relevant field such as Computer Science, Data Science, Statistics, Mathematics, or Engineering (Master’s or PhD is a plus)
• Hands-on experience building and deploying data pipelines and ML models in production environments
• Close familiarity with machine learning, deep learning, NLP/LLMs, and statistical modeling
• Comfortable working with diverse data sources (e.g., APIs, databases, logs, text) and manipulating data using tools such as SQL, Pandas, Spark
• Proficient in Python and common ML/data libraries (e.g., scikit-learn, TensorFlow, PyTorch, pandas, NumPy)
• Strong communication and collaboration skills, with the ability to work across product, engineering, customer success, and marketing teams
• Proven ability to operate independently in ambiguous environments, define scope, and drive projects to impact

Advantage:

• Familiarity with cloud platforms (AWS, GCP, or Azure) and ML lifecycle tooling (e.g., MLflow,, Airflow)
• Familiarity with model evaluation strategies (e.g. A/B testing), containerization (e.g., Docker), model and data monitoring practices.
• Experience deploying and managing machine learning models at scale.
• Domain expertise in Application Security