Job Description:The Senior Machine Learning Scientist develops advanced algorithms and models to extract valuable insights from complex data sets. This role combines deep technical expertise in machine learning with strategic thinking to drive innovation and solve challenging business problems through data-driven approaches.
Job Responsibilities: - Model Development: Design, develop, and implement sophisticated machine learning models and algorithms to address complex business challenges.
- Research Leadership: Lead research initiatives to explore cutting-edge machine learning techniques and methodologies.
- Data Analysis: Analyze large, diverse data sets to identify patterns, trends, and insights that drive business value.
- Cross-Functional Collaboration: Partner with cross-functional teams to understand business requirements and translate them into actionable technical solutions.
- Pipeline Engineering: Develop and optimize data processing pipelines for data preprocessing, feature engineering, model training, and evaluation.
- Data Integration: Evaluate and integrate new data sources to continuously enhance model performance and business insights.
- Performance Monitoring: Continuously monitor production model performance and implement technical improvements as needed.
- Stakeholder Communication: Present complex findings, insights, and recommendations clearly to both technical and non-technical stakeholders.
- Mentorship: Mentor junior data scientists and machine learning engineers, providing technical guidance and driving knowledge sharing across the team.
- Documentation: Create and maintain rigorous documentation for models, methodologies, and technical processes.
Job Qualifications:- Education: Advanced degree (Master's or PhD) in Computer Science, Statistics, Mathematics, a related quantitative field or equivalent work experience.
- Experience: 3+ years of relevant industry work experience.
- Programming & Frameworks: Strong programming skills in Python and extensive experience with machine learning frameworks and libraries (e.g., PyTorch, scikit-learn).
- Production ML: Demonstrated expertise in developing, deploying, and maintaining machine learning models in production environments.
- Cloud & Big Data: Proven experience working with big data technologies and major cloud computing platforms (GCP, AWS, Azure).
- Statistical Proficiency: Strong foundational understanding of statistical analysis, experimental design, and hypothesis testing.
- Data Storytelling: Exceptional verbal, written, and listening skills with a demonstrated ability to communicate complex data insights clearly to diverse audiences.
- Navigating Ambiguity: Excellent problem-solving skills with a proven track record of delivering results while working with ambiguous business requirements.
- Distributed Computing: Hands-on experience with distributed computing frameworks (e.g., Apache Spark, Ray, Dask, or Hadoop) to scale machine learning workloads and process massive datasets.
#LI-Hybrid
Annual Pay Range:111,900 - 130,000 USD
Application Window:This opportunity is expected to remain posted through the date identified below, subject to business needs.
Thrive with CotalityAt Cotality, we offer more than just a job, we provide a benefits experience designed to support your whole self. From a flexible working model to competitive time off and standout health coverage with meaningful perks and growth opportunities, our package is built to help you thrive at work and in life.
Highlights, depending on role classification, include:
- Time off: Generous PTO and 11 paid holidays, plus well-being and volunteer time off.
- Family Support: Up to 16 weeks of fully paid parental leave and a baby stipend.
- Health: Multiple medical plan options with mental health and wellness support offerings.
- Retirement: 401(k) with company match and vesting after one year.
- Financial Perks: $400 annual well-being stipend and tuition assistance up to $5,250.
- Extras: Recognition Rewards, Referral bonuses, exclusive discounts and more!
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