Data Scientist - Remote

We are looking for a talented and experienced Data Scientist to join our dynamic team. As a Data Scientist, you willleverageyour analytical skills andexpertisein machine learning to extract insights from complex datasets and drive data-driven decision-making across our organization. You will collaborate closely with cross-functional teams to develop predictive models, uncover actionable insights, and solve challenging business problems.

Responsibilities

Data Analysis and Exploration

• Analyze large, complex datasets toidentifytrends, patterns, and relationships.
• Conduct exploratory data analysis (EDA) to gain insights and formulate hypotheses.
• Utilize statistical methods and data visualization techniques to communicate findings effectively.

Predictive Modeling and Machine Learning

• Develop and deploy predictive models using machine learning algorithms.
• Perform feature engineering, model selection, and hyperparameter tuning tooptimizemodel performance.
• Evaluate model accuracy, precision, recall, and other performance metrics.

Data Mining and Pattern Recognition

• Apply data mining techniques to extract actionable insights from structured and unstructured data.
• Identify patterns and anomalies in data to detect fraud, predict customer behavior, oroptimizebusiness processes.
• Implement clustering, classification, regression, and other machine learning algorithms as needed.

Experimentation and A/B Testing

• Design and conduct experiments to test hypotheses andvalidatemodel assumptions.
• Implement A/B testing frameworks to evaluate the impact of changes and interventions.
• Analyze experimental results and provide recommendations for further optimization.

Data Integration and API Development

• Build andmaintainintegrations with internal and external data sources and APIs.
• Implement RESTful APIs and web services for data access and consumption.
• Ensure compatibility and interoperability between different systems and platforms.

Collaboration and Communication

• Collaborate with cross-functional teams, including engineers, product managers, and business stakeholders.
• Translate technical findings into actionable insights and recommendations for non-technical audiences.
• Present findings and proposals in clear, concise, and compelling ways.
• Collaborate with analysts and platform teams;participate in reviews, sprints, POCs, and reusable frameworks

Requirements:

• Advanced degree (Master'sor Ph.D.) in Computer Science, Statistics, Mathematics, Economics, or related field.
• Proven experience in data science, machine learning, or predictive analytics roles.
• Proficiency in programming languagescommonlyused in data science (e.g., Python,PySpark,R, etc.).
• Strong understanding of statistical analysis, hypothesis testing, and experimental design.
• Experience with machine learning libraries and frameworks (e.g., Tensor Flow, scikit-learn,PyTorch, etc.).
• Familiarity with data visualization tools and techniques (e.g., Matplotlib,ggplot, Tableau,Power BI,etc.).
• Excellent problem-solving and analytical skills with attention to detail.
• Effective communication and collaboration abilities in a team environment.
• Ability to manage multiple projects and prioritize tasks effectively.
• Exceptional ability to translate complex AI/ML concepts into clear, actionable insights for both technical and non-technical stakeholders.
• Strong collaboration and communication skills to partner effectively with cross-functional teams including business analysts, engineers, and leadership.
• Proficient in producing high-quality technical documentation (design specs, test cases, and user guides) for code and model lifecycle management.
• Oral:
  Ability to collaborate and communicate with a wide range of partners, including IT and business, across all levels of the organization. Must actively manage expectations with stakeholders.
• Problem Solving:
  Must understand the businessneedand develop technical solutions to meet those needs. Innovation, creativity, and critical problem-solving skillsare required tobe successful in this role. Solutions need to be comprehensive, flexible for future changes, and delivered with a high degree of quality.

Equal Opportunity

Employer:

Race, Color, Religion, Sex, Sexual Orientation, Gender Identity, National Origin, Age, Genetic Information, Disability, Protected Veteran Status, or any other legally protected group status.