Senior Data Scientist

Position Name: Senior Data Scientist

Experience: 7 years

Key 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 youll play a pivotal role in revolutionizing our customer acquisition and engagement strategies. Youll 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 longterm data science roadmap focusing on how data can optimize customer experiences and inform product enhancements.
  
• Insights Alchemist: Drive indepth 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.
  
• DataDriven Leader: Translate complex data findings into clear actionable recommendations for product and business decisions.
  
• Scalable Solutions: Design and implement productionready 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 decisionmaking.
  
• TechSavvy 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 cuttingedge 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 problemsolving 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.
  
• Indepth 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!)
  

Key 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)