Senior Data Scientist

2 months ago

Bengaluru, India Carnation Infotech Pvt Ltd Full time
Job DescriptionPosition Name: Senior Data ScientistExperience: 7+ yearsKey Skills to look for:Data Science: Data mining, predictive modeling, time series analysis, machine learning

Big Data: Big data methodologies, data transformation/cleaning (structured & unstructured)

Programming: Python (proficiency essential)

Machine Learning: Deep Learning techniques (LLMs a plus), classical machine learning, A/B testing

Data Storage & Processing: Spark, Hive, distributed data storage systems (Hadoop, BigQuery, EMR) (relational databases a plus: Oracle, SAP, DB2, Teradata, MS SQL Server, MySQL)

Data Visualization: Business intelligence and visualization tools (Tableau, MicroStrategy, Chartio, Qlik) (geospatial data processing a plus)

About the Role:As a Senior Data Scientist, you'll play a pivotal role in revolutionizing our customer acquisition and engagement strategies. You'll leverage your expertise in machine learning and big data to build robust models and lead exploratory analyses that unlock new growth opportunities.

This leadership role demands excellent communication and collaboration skills as you partner with product managers and executives to translate data insights into actionable strategies.Responsibilities:Strategic Visionary: Develop and lead the long-term data science roadmap, focusing on how data can optimize customer experiences and inform product enhancements.

Insights Alchemist: Drive in-depth analysis of user behavior and the broader ecosystem, identifying key levers to improve core metrics and develop predictive models.

Model Maestro: Shape and influence the development and implementation of data and machine learning models, maximizing user experience and uncovering new avenues for innovation.

Data-Driven Leader: Translate complex data findings into clear, actionable recommendations for product and business decisions.

Scalable Solutions: Design and implement production-ready machine learning algorithms for big data environments.

Discovery Champion: Spearhead exploratory data analysis projects that reveal hidden patterns and unlock potential for growth and optimization.

Data Detective: Answer critical business questions by leveraging big data to analyze trends, identify root causes, and optimize products and services.

Metrics Mastermind: Define and track key performance indicators (KPIs) to measure project success.

Experimentation Expert: Design, conduct, and analyze A/B tests to validate hypotheses and inform decision-making.

Tech-Savvy Innovator: Continuously explore and evaluate new data processing technologies, staying at the forefront of industry best practices.

Large Language Champion: Build and deploy innovative applications leveraging cutting-edge large language models (LLMs). (Optional, if applicable)

Qualifications:7+ years of experience in data science, encompassing data mining, predictive modeling, time series analysis, machine learning, big data methodologies, and data transformation/cleaning (structured and unstructured).

Advanced degree (PhD preferred) in a quantitative discipline (Physics, Statistics, Mathematics, Engineering, or Computer Science).

Deep expertise in Deep Learning techniques (experience with LLMs a significant plus).

Proven problem-solving and coding skills (Python proficiency essential).

Strong understanding of A/B testing, classical machine learning, and deep learning.

Solid foundation in recommendation systems, ranking, and retrieval algorithms.

In-depth knowledge of Python, SQL, Spark, and Hive.

Demonstrated experience with distributed data storage systems like Hadoop, BigQuery, EMR, Hive, etc. (Familiarity with relational databases like Oracle, SAP, DB2, Teradata, MS SQL Server, and MySQL is a plus).

Experience with business intelligence and visualization tools (Tableau, MicroStrategy, Chartio, Qlik) is a plus. (Bonus points for geospatial data processing skills)

RequirementsKey Skills to look for: Data Science: Data mining, predictive modeling, time series analysis, machine learning Big Data: Big data methodologies, data transformation/cleaning (structured & unstructured) Programming: Python (proficiency essential) Machine Learning: Deep Learning techniques (LLMs a plus), classical machine learning, A/B testing Data Storage & Processing: Spark, Hive, distributed data storage systems (Hadoop, BigQuery, EMR) (relational databases a plus: Oracle, SAP, DB2, Teradata, MS SQL Server, MySQL) Data Visualization: Business intelligence and visualization tools (Tableau, MicroStrategy, Chartio, Qlik) (geospatial data processing a plus)

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