RockCreek is a leading global investment management firm that applies data-driven technology and innovation to sustainable investing. Our portfolio managers invest in emerging markets and alternatives, and our asset allocation teams invest in multi-asset classes and provide outsourced CIO services as well as customized solutions. RockCreek’s client base is made up of sophisticated institutional investors, including endowments, foundations, pension plans, and sovereign funds. The firm is highly focused on the integration of environmental, social, and governance (ESG) factors and sustainable impact across portfolios to generate long-term returns. RockCreek is a collaborative environment that values openness, transparency, partnership, and knowledge sharing. Diversity, debate and a relentless drive to excel are foundations of our team culture.

Technology is a key, and growing, part of our service offerings. We are committed to best-of-breed applications, automation, and solutions for managing funds and portfolios across our broad range of investment offerings. In addition to launching a dedicated advanced analytics team, we are currently consolidating our data assets into a large data lake on Amazon Web Services and providing a variety of API and programmatic access patterns.

RockCreek seeks a Data Scientist to apply innovative data-driven methods and advanced analytics to informed investment choices and expand our leadership in ESG investing. As one of the founding members of our expanded analytics team, you will play a leading role in designing our data architecture, building models, pioneering new metrics, visualizing data, and creating models to improve performance across RockCreek. The right candidate will have an inquisitive mind for understanding the power and limitations of data, an entrepreneurial approach to building new tools and applications, and a passion for responsibly harnessing data to drive impactful investment decisions.

This position is based in RockCreek’s Washington, DC, office. Frequent travel is not expected. You may occasionally travel to our New York office or interact with partner organizations.

Qualifications

• Minimum of 2-3 years of experience using applying data and advanced analytics tools in a business or academic setting
• Advanced degree (Masters or Ph.D.) in a relevant field or equivalent experience (e.g., relevant certificate or training)
• Deep experience solving analytical problems through data-driven, quantitative approaches, including statistical methods, machine learning techniques, and predictive models
• Experience translating user requirements, diverse data, and advanced algorithms into actionable, understandable insights for non-technical users
• Proven track record working cross-functionally and collaborating with engineering, client services, and reporting teams to balance multiple projects and stakeholders
• Entrepreneurial, comfortable carrying projects from blueprinting to scoping and implementation by collaborating cross-functionally
• Exceptional curiosity and problem solving, with a real passion for catalyzing impact with analytics
• Excellent organizational and communication skills
• Strong understanding of financial concepts and data, with direct experience developing and evaluating financial industry models preferred
• Demonstrated commitment to diversity and respect differences in race, ethnicity, age, gender identity and expression, sexual orientation, religion, ability, and socio-economic circumstance
• A collaborative and respectful attitude toward resolving obstacles and conflicts

Technical Requirements:

• Fluency with modeling in Python, R, Scala, or similar programming languages
• Experience with relational database applications and integrations, knowledge of ETL tools and pipelines preferred
• Familiarity with Linux/Unix/BSD command-line tools and shell scripting
• Experience with and passion for data visualization techniques and concepts
• Experience with big data frameworks and deep learning toolkits preferred
• Experience and community involvement with open-source applications preferred
• Experience evaluating data quality, model bias, and algorithm accuracy

• Minimum of 2-3 years of experience using applying data and advanced analytics tools in a business or academic setting
• Advanced degree (Masters or Ph.D.) in a relevant field or equivalent experience (e.g., relevant certificate or training)
• Deep experience solving analytical problems through data-driven, quantitative approaches, including statistical methods, machine learning techniques, and predictive models
• Experience translating user requirements, diverse data, and advanced algorithms into actionable, understandable insights for non-technical users
• Proven track record working cross-functionally and collaborating with engineering, client services, and reporting teams to balance multiple projects and stakeholders
• Entrepreneurial, comfortable carrying projects from blueprinting to scoping and implementation by collaborating cross-functionally
• Exceptional curiosity and problem solving, with a real passion for catalyzing impact with analytics
• Excellent organizational and communication skills
• Strong understanding of financial concepts and data, with direct experience developing and evaluating financial industry models preferred
• Demonstrated commitment to diversity and respect differences in race, ethnicity, age, gender identity and expression, sexual orientation, religion, ability, and socio-economic circumstance
• A collaborative and respectful attitude toward resolving obstacles and conflicts

Technical Requirements:

• Fluency with modeling in Python, R, Scala, or similar programming languages
• Experience with relational database applications and integrations, knowledge of ETL tools and pipelines preferred
• Familiarity with Linux/Unix/BSD command-line tools and shell scripting
• Experience with and passion for data visualization techniques and concepts
• Experience with big data frameworks and deep learning toolkits preferred
• Experience and community involvement with open-source applications preferred
• Experience evaluating data quality, model bias, and algorithm accuracy

Mission Statement:

RockCreek is a leading global investment management firm that applies data-driven technology and innovation to sustainable investing. We believe sustainability and diversity generate superior performance by investing in long term value. We have stable and long‐term partnerships with our clients and companies and attract the best mission‐oriented team. Sustainable investing extends throughout our investments, our diverse team and culture, our office environment, operations and travel.

ESG Policy:

Since our founding, RockCreek’s commitment to sustainable investing, long term value creation, and good governance has begun at home. We believe RockCreek’s entrepreneurial spirit, open culture, and diverse team lead to better investments on behalf of the universities, foundations, pension plans, and sovereign funds that partner with us. The way we operate our offices, procure services, and partner with stakeholders are all in keeping with our aim to have a positive impact on markets globally and reduce our carbon footprint. This strong stable culture values diversity and inclusion as well as a commitment to investing responsibly for long term returns. RockCreek is among the largest woman-founded firms in the world. Its founders have a deep commitment to sustainability as well as long experience with sustainable impact investing and ESG policies that date back to 1980s. This includes investing in energy, health, technology and financial inclusion.

RockCreek is a collaborative environment that values openness, transparency, partnership, and knowledge sharing. In a typical day you will interact with members of all of our teams; engineering is neither siloed nor cut off from the overall RockCreek business. You should be both interested and capable of learning the investment business as it relates to engineering, and creatively looking to enhance the overall RockCreek service offerings.