Lead Data Scientist

We are searching for a skilled and enthusiastic Lead Data Scientist to join our innovative team.

This role involves leveraging advanced statistical models, machine learning, and data analysis to extract actionable insights, create predictive models, and influence business outcomes. It offers an exciting opportunity to engage with diverse datasets, cloud technologies, and modern tools to solve challenging problems while collaborating with cross-functional stakeholders.

Responsibilities

• Apply mathematical, statistical, and machine learning methods to derive insights and support decisions
• Leverage frameworks like TensorFlow and PyTorch for predictive and prescriptive model development
• Identify and validate internal and external data sources to uncover patterns and business opportunities
• Formulate and test hypotheses by working with analytics sandboxes and enhancing models iteratively
• Utilize tools such as Pandas, NumPy, and Scikit-learn for data manipulation and analysis
• Collaborate with cross-functional teams to prepare and clean data effectively for analysis
• Manage datasets within relational databases using SQL and ensure compliance with governance standards
• Create impactful data visualizations using Matplotlib, Seaborn, or Plotly
• Align data models and practices with organizational data strategy and adhere to best practices
• Deploy machine learning models into production environments via cloud platforms like Amazon SageMaker and EC2
• Partner with engineers and stakeholders to implement scalable solutions for handling data workloads

Requirements

• At least 5 years of experience in data science, machine learning, or applicable fields
• Proficiency in Python, including use of libraries such as Pandas, NumPy, and Scikit-learn
• Knowledge of machine learning frameworks, such as TensorFlow or PyTorch
• Skills in cloud platforms like AWS, including services like S3 and SageMaker
• Background in using big data technologies like Spark, relational databases with SQL, and Jupyter
• Familiarity with version control tools such as Git
• Understanding of natural language processing (NLP) techniques and sentiment analysis approaches
• Proficiency in open-source data science tools, libraries, and frameworks
• Competency in data visualization standards with tools like Matplotlib, Seaborn, or Plotly
• Familiarity with data governance principles to ensure compliance and data quality

Nice to have

• Knowledge of Docker for containerization and deployment processes
• Expertise in Snowflake for advanced analytics and data warehousing
• Flexibility to use tools in the Atlassian suite, including Bitbucket, JIRA, and Confluence
• Understanding of simulation methods, complex event processing, and scenario-driven analytics

We offer

• Competitive compensation depending on experience and skills
• Variety of projects within one company
• Being a part of a project following engineering excellence standards
• Individual career path and professional growth opportunities
• Internal events and communities
• Flexible work hours