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Technology Consulting Data Science Senior
KPMG India
posted 1mon ago
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Flexible timing
Key skills for the job
Job Description
About KPMG in India
.
Major Duties Responsibilities
Work with business stakeholders and cross-functional SMEs to deeply understand business context and key business questions Create Proof of concepts (POCs) / Minimum Viable Products (MVPs), then guide them through to production deployment and operationalization of projects Influence machine learning strategy for Digital programs and projects Make solution recommendations that appropriately balance speed to market and analytical soundness Explore design options to assess efficiency and impact, develop approaches to improve robustness and rigor Develop analytical / modelling solutions using a variety of commercial and open-source tools (e.g., Python, R, TensorFlow) Formulate model-based solutions by combining machine learning algorithms with other techniques such as simulations. Design, adapt, and visualize solutions based on evolving requirements and communicate them through presentations, scenarios, and stories. Create algorithms to extract information from large, multiparametric data sets. Deploy algorithms to production to identify actionable insights from large databases. Compare results from various methodologies and recommend optimal techniques. Design, adapt, and visualize solutions based on evolving requirements and communicate them through presentations, scenarios, and stories. Develop and embed automated processes for predictive model validation, deployment, and implementation Work on multiple pillars of AI including cognitive engineering, conversational bots, and data science Ensure that solutions exhibit high levels of performance, security, scalability, maintainability, repeatability, appropriate reusability, and reliability upon deployment Lead discussions at peer review and use interpersonal skills to positively influence decision making Provide thought leadership and subject matter expertise in machine learning techniques, tools, and concepts; make impactful contributions to internal discussions on emerging practices Facilitate cross-geography sharing of new ideas, learnings, and best-practices
Required Qualifications
Bachelor of Science or Bachelor of Engineering at a minimum. 3-6 years of work experience as a Data Scientist A combination of business focus, strong analytical and problem-solving skills, and programming knowledge to be able to quickly cycle hypothesis through the discovery phase of a project Advanced skills with statistical/programming software (e.g., R, Python) and data querying languages (e.g., SQL, Hadoop/Hive, Scala) Good hands-on skills in both feature engineering and hyperparameter optimization Experience producing high-quality code, tests, documentation Experience with Microsoft Azure or AWS data management tools such as Azure Data factory, data lake, Azure ML, Synapse, Databricks Understanding of descriptive and exploratory statistics, predictive modelling, evaluation metrics, decision trees, machine learning algorithms, optimization forecasting techniques, and / or deep learning methodologies Proficiency in statistical concepts and ML algorithms Good knowledge of Agile principles and process Ability to lead, manage, build, and deliver customer business results through data scientists or professional services team Ability to share ideas in a compelling manner, to clearly summarize and communicate data analysis assumptions and results Self-motivated and a proactive problem solver who can work independently and in teams
B.Tech/M.Tech/MCA/M.Sc
About KPMG in India
.
Major Duties Responsibilities
Work with business stakeholders and cross-functional SMEs to deeply understand business context and key business questions Create Proof of concepts (POCs) / Minimum Viable Products (MVPs), then guide them through to production deployment and operationalization of projects Influence machine learning strategy for Digital programs and projects Make solution recommendations that appropriately balance speed to market and analytical soundness Explore design options to assess efficiency and impact, develop approaches to improve robustness and rigor Develop analytical / modelling solutions using a variety of commercial and open-source tools (e.g., Python, R, TensorFlow) Formulate model-based solutions by combining machine learning algorithms with other techniques such as simulations. Design, adapt, and visualize solutions based on evolving requirements and communicate them through presentations, scenarios, and stories. Create algorithms to extract information from large, multiparametric data sets. Deploy algorithms to production to identify actionable insights from large databases. Compare results from various methodologies and recommend optimal techniques. Design, adapt, and visualize solutions based on evolving requirements and communicate them through presentations, scenarios, and stories. Develop and embed automated processes for predictive model validation, deployment, and implementation Work on multiple pillars of AI including cognitive engineering, conversational bots, and data science Ensure that solutions exhibit high levels of performance, security, scalability, maintainability, repeatability, appropriate reusability, and reliability upon deployment Lead discussions at peer review and use interpersonal skills to positively influence decision making Provide thought leadership and subject matter expertise in machine learning techniques, tools, and concepts; make impactful contributions to internal discussions on emerging practices Facilitate cross-geography sharing of new ideas, learnings, and best-practices
Required Qualifications
Bachelor of Science or Bachelor of Engineering at a minimum. 3-6 years of work experience as a Data Scientist A combination of business focus, strong analytical and problem-solving skills, and programming knowledge to be able to quickly cycle hypothesis through the discovery phase of a project Advanced skills with statistical/programming software (e.g., R, Python) and data querying languages (e.g., SQL, Hadoop/Hive, Scala) Good hands-on skills in both feature engineering and hyperparameter optimization Experience producing high-quality code, tests, documentation Experience with Microsoft Azure or AWS data management tools such as Azure Data factory, data lake, Azure ML, Synapse, Databricks Understanding of descriptive and exploratory statistics, predictive modelling, evaluation metrics, decision trees, machine learning algorithms, optimization forecasting techniques, and / or deep learning methodologies Proficiency in statistical concepts and ML algorithms Good knowledge of Agile principles and process Ability to lead, manage, build, and deliver customer business results through data scientists or professional services team Ability to share ideas in a compelling manner, to clearly summarize and communicate data analysis assumptions and results Self-motivated and a proactive problem solver who can work independently and in teams
Employment Type: Full Time, Permanent
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21% candidates got the interview through other sources.
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Data Science salary at KPMG India
reported by
1
employee
with 10
years exp.
₹22.5
L/yr - ₹28.8
L/yr
396%
more
than the average Data Science Salary in India
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What KPMG India employees are saying about work life
based on 5.1k employees
Flexible timing
Monday to Friday
No travel
Day Shift
KPMG India Benefits
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