Data Scientist_Python (3-5 years)
Budget: ₹150,000 – ₹250,000 INR
Hello,
This position will be responsible for applying AI/ML techniques on data and generate insights that identify recent trends/relationships in data and bring improvement/automations into the process if required.
Note - The Person has to be available to join immediately.
Minimum Qualifications
Degree in applied quantitative discipline (e.g. Economics, Statistics, Mathematics, Computational Science)
Responsibilities
Data preparation and validation :
Prepare data for processing by organizing information, checking for any inaccuracies, and adjusting and weighting the raw data.
Evaluate the statistical methods and procedures used to obtain data in order to ensure validity, applicability, efficiency, and accuracy.
Identify relationships and trends in data, as well as any factors that could affect the results of model.
Work on AI/ML techniques and provide insights to stakeholder.
Bring automation to the process wherever applicable.
Requirements
Strong Knowledge of analytical, quantitative and qualitative skills
Hands on experience on supervised and unsupervised machine learning techniques.
Ability to work independently
Tools used for analysis :
Running statistical models or/and machine learning algorithms using Python/R/SPSS /SAS (expert in two of them is a must)
Knowledge on SQL, Hive will be plus
Knowledge on Tableau ,R Shiny and Python Dash
Extensive knowledge on advanced MS Excel and MS Power point.
Techniques typically used for analysis are :
Clustering
Classification - Decision Tree, Random Forest, XGBOOST, BERT, Support Vector Machines Naïve Bayes etc.
Regularization
Strong Client Communication :
Communicate results to stakeholders in requested format such as graphs, charts, and tables.
Adapt statistical methods to provide end to end business solution
In this role, the candidate may have to work during global hours in order to connect with other teams working in different time zones.
This position will be responsible for applying AI/ML techniques on data and generate insights that identify recent trends/relationships in data and bring improvement/automations into the process if required.
Note - The Person has to be available to join immediately.
Minimum Qualifications
Degree in applied quantitative discipline (e.g. Economics, Statistics, Mathematics, Computational Science)
Responsibilities
Data preparation and validation :
Prepare data for processing by organizing information, checking for any inaccuracies, and adjusting and weighting the raw data.
Evaluate the statistical methods and procedures used to obtain data in order to ensure validity, applicability, efficiency, and accuracy.
Identify relationships and trends in data, as well as any factors that could affect the results of model.
Work on AI/ML techniques and provide insights to stakeholder.
Bring automation to the process wherever applicable.
Requirements
Strong Knowledge of analytical, quantitative and qualitative skills
Hands on experience on supervised and unsupervised machine learning techniques.
Ability to work independently
Tools used for analysis :
Running statistical models or/and machine learning algorithms using Python/R/SPSS /SAS (expert in two of them is a must)
Knowledge on SQL, Hive will be plus
Knowledge on Tableau ,R Shiny and Python Dash
Extensive knowledge on advanced MS Excel and MS Power point.
Techniques typically used for analysis are :
Clustering
Classification - Decision Tree, Random Forest, XGBOOST, BERT, Support Vector Machines Naïve Bayes etc.
Regularization
Strong Client Communication :
Communicate results to stakeholders in requested format such as graphs, charts, and tables.
Adapt statistical methods to provide end to end business solution
In this role, the candidate may have to work during global hours in order to connect with other teams working in different time zones.