Senior Data Scientist (ML)

Job Description:

The Senior Data Scientist is a creative, open-minded problem solver with effective time management and communication skills. Will be responsible for collaboratively working with our stakeholders to manage engagements and lead teams of data and analytics resources in all aspects of design and delivery of data and analytics solutions - including Analytics, Data Visualization, and Data Management.

We are seeking a candidate with experience in time series forecasting methods, and prior work on network science projects. Experience with Google Cloud Platform (GCP) for AI/ML, BigQuery and Vertex AI is also required.

Project Overview:

Goal: Build an ML pipeline for data cleaning and more.

Key Requirements:

• RAG (Retrieval-Augmented Generation) will be a key technique in the process

Technical Skills & Tools:

• Experience with GCP, BigQuery, and Vertex AI is important for implementing the solution.

Duties & Responsibilities:

• Learn and understand a broad range of data resources and know when, how, and which to use and which not to at any given time.
• Manipulate and analyze complex, high-volume, high-dimensionality data from various sources using a variety of tools, data analysis techniques, and data science methodology, and use them to identify trends and reach meaningful conclusions.
• Design data modelling processes to create algorithms and predictive models and perform custom analysis.
• Design, build, deploy, produce, and operate life cycles of machine learning pipelines.
• Partner with customers to define and execute the critical insights required to make informed business decisions
• Be a hands-on technical lead who can own, drive, and develop insights from conception to release
• Act as a catalyst for insights innovation, aligned to both tactical and strategic business insights efforts
• Ensuring insights are both actionable and measurable and you should be able to build these insights and hypothesis with awareness of practical implementation and implications for the business
• Empower and mentor existing employees to further the team’s data science capabilities and capacity

Work Experience:

• 5 to 7 years of hands-on experience with data science and analytics tools.
• Proven success in applying data science methodologies to support business outcomes.
• Extensive knowledge in statistical methods and data mining.

Education Level:

• Bachelor’s degree or PhD in an analytical area such as Mathematics, Statistics, Engineering, Machine Learning, Artificial intelligence, or relevant fields with experience in working with AI, ML and Data Science

Knowledge, Skills, Abilities:

• Experience with general ML methods and expert in some of the following field:

o  Recommendation Systems

o  Supervised learning and feature engineering

o  Time series and forecasting analysis

o  Clustering

• Experience with projects of network science
• Extensive experience with feature engineering
• Experience of getting insights by overlaying multiple datasets
• Proficient in a data science language like Python, R, Scala
• Proficient with machine learning packages like scikit-learn, TensorFlow etc.
• Experience with Cloud base AI/ML tools and data analytics tools in GCP is preferable
• Experience with the build, deploy, produce, and operate life cycles of machine learning pipelines.
• Experience working with large, distributed data sets to derive actionable insight
• Familiar with Power BI / Google Looker dashboard development
• Interpersonal communication and ability to leverage the data to tell a story
• Collaboration and program management skills
• Logical & systematic, team player, fast learner
• Familiar with Agile and working in a Scrum Team