Data Scientist - PhD , Bengaluru, Karnataka, India

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Company Description

About Affine

Affine is a Data Sciences & AI services provider, offering capabilities across the analytical value chain from data engineering to analytical modelling and business intelligence to solve strategic & day to day business challenges of organizations worldwide. They empower their clients to make informed decisions & to take proactive actions through impeccable technology-based development & business acumen.

They develop solutions for multiple verticals such as Retail, CPG, E-commerce, High-Technology, BFSI, Media & Entertainment, Manufacturing among others and are respected as one of the Marquee names in the “Consultancies for Transformation” space.

Affine is headquartered in Bengaluru, India with other offices in New York & Seattle, United States and Singapore.

Job Description

Experience : 0 – 4 years
Education requirement: PhD in Machine Learning/Deep Learning/Artificial Intelligence/Image
processing/Statistics/Computer Science/ Mathematics

Responsibilities
• Utilizing artificial intelligence and machine learning concepts to solve challenging business problems
• Work on problems from various domains like NLP, Recommendation engine, computer vision
• Should participate in complete project cycle i.e. understanding a problem statement, data gathering,
analyzing data, implementing ML/AI solutions
• Should be able to learn new tools/languages quickly and continue expanding knowledge on latest
advances in ML/AI
• Managing project timing, client expectations and meeting deadlines
• Publishing research articles, papers and blogs

Desired skills and experience:
•Strong experience in machine learning/artificial intelligence in academics or academics plus
industry
• Expert level in at least one programming language. Preferably R or Python
• Knowledge of statistics and machine learning (Probability theory, parametric and non-parametric
models, supervised and unsupervised ML techniques, etc.)
• Knowledge of deep learning algorithms (CNN, RNN, autoencoders, etc.)
• Knowledge in databases preferable

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