Senior Data Scientist - Remote

Role Overview:

We are looking for a Senior Data Scientist who will be part of a critical and highly visible role to join our team of Data Scientists. Are you looking to make an impact in Data Science and Analytics? Come be a part of the change as we move into a new era here at McAfee. Mission driven, both at company and functional level, we share a passion for customers at the core. You will report to the Senior Manager of Data Science (Machine Learning). Data Science at McAfee is going through an exciting phase its a great time to jump in!

This is a remote position in India. We will only consider candidates currently in India and are not offering relocation assistance at this time.

About the role:

Develop, implement, and deploy machine learning models that leverage our unique combination of user behavior and subscription data to improve consumer value from our products.
Deliver intelligent personalization and recommendation products in all our touch points consumer including marketing, product, and customer service.
Mine, analyze and build predictive and descriptive machine learning models on structured and unstructured data sources.
Utilize code (Python, R, Scala, etc.) for analyzing data and building statistical models to solve business problems.
Apply or design highly innovative models for predictive learning, forecasting, recommendations, content ranking, and anomaly detection.
Create algorithms for optimizing consumer journey and increasing conversion and monetization.
Perform statistical analysis on the outputs of these machine learning models to help update, re-train, and then deploy new ML models.
Contribute to the creation, deployment, and scaling of machine learning and predictive algorithms in a production environment.


About You:

You will have 5+ years of experience in one or more of the following areas: machine learning (including deep learning), recommendation systems, pattern recognition, data mining or artificial intelligence.
M.S. or PhD in Computer Science or Machine Learning related degree; or equivalent work experience in the field.
Experience with various ML techniques and frameworks, e.g., data discretization, normalization, sampling, linear regression, decision trees, deep neural networks, etc.
You will be proficient with designing, analyzing, and troubleshooting controlled experiments (Causal A/B tests, Multivariate tests).
Proficient with applied machine learning techniques and intermediate data engineering skill set with tools, libraries, or frameworks such as R, Python, SQL, MapReduce, Hadoop, Hive and Big Data technologies, scikit-learn, Keras, TensorFlow, PyTorch etc.
You will work with enormous amounts of structured and unstructured data in a consumer facing online business.
You will have algorithmic problem-solving skills and practical experience with machine learning.
You will work with natural language processing (NLP), text mining, statistical modeling, and hypothesis testing.
#LI- Remote
Company Overview


McAfee is a leader in personal security for consumers. Focused on protecting people, not just devices, McAfee consumer solutions adapt to users needs in an always online world, empowering them to live securely through integrated, intuitive solutions that protects their families and communities with the right security at the right moment.



Company Benefits and Perks:


We work hard to embrace diversity and inclusion and encourage everyone at McAfee to bring their authentic selves to work every day. We offer a variety of social programs, flexible work hours and family-friendly benefits to all of our employees.
Bonus Program
Pension and Retirement Plans
Medical, Dental and Vision Coverage
Paid Time Off
Paid Parental Leave
Support for Community Involvement

We're serious about our commitment to diversity which is why McAfee prohibits discrimination based on race, color, religion, gender, national origin, age, disability, veteran status, marital status, pregnancy, gender expression or identity, sexual orientation or any other legally protected status.