Senior Data Scientist
Atrium
- Boston, Massachusetts, United States
- Boston, Massachusetts, United States
About
Collaborate with investment teams to design, build, and deploy predictive and explanatory models that inform critical investment decisions. Productionization & Maintenance:
Implement models in production environments; monitor, maintain, and enhance model performance and reliability over time. Business Problem Translation:
Engage with business stakeholders to understand challenges, formulate analytical approaches, and translate needs into effective data-driven solutions. Data Visualization & Analytics:
Develop compelling dashboards and visualizations to deliver insights and support decision-making. Continuous Improvement:
Stay abreast of advancements in data science, machine learning, and analytics; proactively recommend and implement improvements to existing workflows and models. Stakeholder Communication:
Communicate technical concepts and analytical findings to both technical and non-technical audiences; advocate for data-driven decision making across the organization. Cross-Functional Collaboration:
Partner with data engineering teams to design, implement, and optimize robust data pipelines and infrastructure, ensuring reliable, scalable access to high-quality data for modeling and analytics. Qualifications Bachelor’s or Master’s degree in a quantitative field (e.g., Computer Science, Statistics, Mathematics, Engineering, Data Science, or related discipline). 5+ years of hands-on experience as a data scientist, analytics professional, or in a similar role. Required Skills Proven experience designing, building, and deploying models for real-world business applications, ideally in fast-paced, high-stakes environments. Deep expertise in Python and SQL for data analysis, modeling, and workflow automation. Strong foundation in both predictive (e.g., regression, classification, forecasting) and explanatory (e.g., causal inference, interpretability) modeling techniques, leveraging standard ML and statistical libraries (e.g., scikit-learn, XGBoost, statsmodels). Exceptional communication skills, with the ability to distill complex technical concepts for diverse audiences. Experience working with generative AI models to develop, evaluate, and deploy solutions that leverage text, image, or other unstructured data. Expertise in data visualization and analytics, with hands-on experience using BI tools (e.g. Tableau or Sigma) to interface with business users. Experience productionizing models and working within modern data science toolchains, using tools such as MLflow, Airflow, or similar for workflow management and monitoring. Strong business judgment, intellectual curiosity, and collaborative spirit. Preferred Skills Expertise in Bayesian statistical modeling is highly desired. Experience in finance, investment, or management consulting. Familiarity with cloud platforms (e.g., AWS) and modern data engineering practices. Pay range and compensation package 175000 - 200000 [Pay range or salary or compensation] Bonus and profit sharing Equal Opportunity Statement [Include a statement on commitment to diversity and inclusivity.]
Languages
- English
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