Software Engineer II

Job Description:
Designation / Title
Data Scientist II
Experience (Years)
4+ Yrs
Joining Location
Pune
About Quick Heal
Quick Heal Technologies Ltd, founded in
1995 and headquartered in Pune, is India’s leading listed cybersecurity
solutions provider with 23 offices and 1,000+ professionals. Through its
enterprise arm Seqrite,
the company delivers cutting-edge Zero Trust solutions to secure endpoints, data, networks, and users across industries and geographies.
Seqrite Labs powers its
offerings with advanced threat research, intelligence, and real-time
detection. Notably, Seqrite secured ISRO’s command & control center
during the Chandrayaan 3 mission. Its services division provides
consulting to corporates, PSUs, government, and law enforcement agencies
worldwide.
Core Purpose: Innovate to simplify digital
security
Vision: To be trusted globally as a cybersecurity leader
Mission: Empower teams to solve business problems
Seqrite stands out as a
purpose-led organization that invests in people, fosters innovation, and
offers opportunities to work on new technologies while building a safer
digital world.
Job Summary
(A brief overview of the role, its purpose, and key
responsibilities.)
The Data Scientist will
be responsible for analyzing data, building machine learning models, and
generating insights to support cybersecurity and product use cases. The role
involves data preprocessing, feature engineering, model development, model
evaluation, and working with engineering teams to integrate ML outputs into
applications, dashboards, or workflows.
The candidate should have
hands-on experience in Python, SQL, machine learning techniques, data
analysis, and basic MLOps concepts. Experience in cybersecurity analytics,
anomaly detection, user behavior analytics, or AI/ML-based product
development will be an added advantage.
Job Responsibilities
(The key tasks and duties you will be expected to perform in this
role.)
· Understand business and
product requirements and convert them into data analysis or machine learning
tasks.
· Collect, clean,
preprocess, and analyze structured and unstructured datasets from different
sources.
· Perform exploratory data
analysis to identify trends, patterns, anomalies, and useful insights.
· Build and validate
machine learning models for classification, prediction, clustering, anomaly
detection, and risk scoring use cases.
· Perform feature
engineering to improve model accuracy and business relevance.
· Evaluate model
performance using suitable metrics such as accuracy, precision, recall,
F1-score, and false positive rate.
· Work with engineering
teams to integrate ML models or analytical outputs into products, APIs,
reports, or dashboards.
· Support model
deployment, monitoring, retraining, and performance tracking using basic
MLOps practices.
· Prepare reports,
visualizations, and documentation to communicate findings and model outcomes.
· Collaborate with
product, engineering, security, and data teams to deliver practical
data-driven solutions.
· Maintain proper
documentation for datasets, model logic, assumptions, evaluation results, and
limitations.
·
Continuously learn and apply relevant AI/ML techniques, tools, and
frameworks based on project needs.
·
Strong communication, troubleshooting, co-ordination and interpersonal skill
Must Have Skills
(The essential skills and expertise required to succeed in this role.)
· Bachelor’s/Master’s
degree in Computer Science, Data Science, Statistics, Mathematics,
Engineering, or equivalent.
· 3–6 years of hands-on
experience in Data Science, Machine Learning, or AI/ML solution development.
· Strong programming
skills in Python.
· Good knowledge of SQL
and experience working with structured/unstructured datasets.
· Hands-on experience with
data preprocessing, feature engineering, exploratory data analysis, and model
evaluation.
· Good understanding of ML
algorithms such as classification, regression, clustering, anomaly detection,
and predictive modeling.
· Experience with Python
libraries such as Pandas, NumPy, Scikit-learn, and visualization
libraries.
· Basic understanding of MLOps,
including model deployment, monitoring, retraining, and versioning.
· Ability to analyze data,
identify patterns, and present insights clearly.
· Good communication,
documentation, and cross-functional collaboration skills.
Nice / Good to have skills
(Additional skills that are not mandatory but give you an added
advantage in this role.)
·
Exposure to cybersecurity
·
Exposure to Generative AI, LLMs, RAG, prompt engineering, or Agentic AI
concepts.
· Experience with
dashboa

Experience
3 - 6 Years

Employment type
Full Time

Work arrangement
No