Roles &amp; Responsibilities:

• Identify potential issues within the system and suggest solutions with guidance from senior team members.

• Gain understanding of project requirements and contribute to scoping existing and new requirements.

• Collaborate with internal stakeholders and cross-functional teams to assist in the development of solutions.

• Assist in identifying and analyzing user behavior on the platform.

• Assist in data pre-processing, cleansing, transformation, and verification processes.

• Assist in selecting relevant features for machine learning models under supervision.

• Support in building basic unsupervised and supervised learning algorithms toenhance system responsiveness.

• Contribute to the deployment of machine learning models and participate in monitoring their performance.

• Participate in optimizing and evaluating models on test and train datasets.

• Contribute to projects related to customer analytics, segmentation, user journey prediction, recommendation systems, lead generation, and basic image processing algorithms under mentor-ship. 
Must Have:

• Proficiency in Python/Pyspark, SQL.

• Experience with common data science toolkits such as pandas, numpy, scipy, scikit- learn, and matplotlib.

• Strong understanding of statistical concepts including probability, conditional probability, probability distribution, sampling, estimation, and hypothesis testing.

• Experience with various machine learning techniques and algorithms including Regression, Decision Trees, Random Forest, XGBoost, k-NN, Naive Bayes, SVM, and Recommender systems.

• Excellent problem-solving and analytical skills with a keen eye for identifying patterns and insights in complex datasets.

• Minimum of bachelor’s degree in a relevant discipline. 
Good to Have:

• Experience with Generative AI framework for instance OpenAI, Azure OpenAI, Huggingface e.t.c.

• Experience with deep learning models like ANN, RNN, and CNN.

• Experience with deep learning frameworks such as Pytorch and Tensorflow.

• Experience with NoSQL databases such as MongoDB, Cassandra, HBase.

• Knowledge of Big data algorithms and Data Lake.

• Knowledge of AutoML models like H2o and Pycaret.

• Experience in building NLP models.

• Good command of UNIX.

• Any post-graduate education/certification in statistics, AI, or related fields is preferred.

Data Scientist

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Skills Required for Data Scientist

Job Description for Data Scientist