Actif.ai, Inc.
Data Scientist – All Experience Levels
Actif.ai, Inc., Washington, District of Columbia, us, 20022
Actifai is seeking experienced data scientists.The Data Scientist will participate as a key team member in envisioning, designing, coding, testing, and improving the algorithms that are central to our mission as a company. They will work in continual collaboration with software engineers and partner company stakeholders.The CompanyActifai is an artificial intelligence company. We help clients – primarily those in the cable and telecom industry – optimize their high value, high leverage decisions. Typically this includes things like customer acquisition, customer retention, and customer development (upsells/cross-sells).Actifai is part of Foundry.ai, a technology fund/studio that creates AI software companies in partnership with large global enterprises. Foundry’s operating companies focus on practical applications of AI that drive immediate, measurable, and recurring improvements to financial performance. Foundry is backed by approximately $100MM in capital from leading private equity and venture capital partners.The PositionThe Data Scientist will participate as a key team member in envisioning, designing, coding, testing, and improving the algorithms that are central to our mission as a company. They will work in continual collaboration with software engineers and partner company stakeholders.
Some key challenges will include: identifying external datasets and developing API or other methods for accessing them; fluidly self-educating on existing methods for modeling end-user behavior in a variety of contexts, or developing new methods for doing this when necessary; designing experiments to answer targeted questions; teaming with developers to embed algorithms in applications; understanding business economics, user motivation and other contextual information in order to guide analytical trade-offs, with a focus on “minimum viable algorithm” followed by intensive, iterative improvement; writing code that builds new companies and products.
Entry level candidates will likely have many of the following characteristics:Comfortable using scripting languages, and relational or NoSQL databases.Familiar with general-purpose machine learning methods, such as regression, decision trees, neural networks, Bayesian networks, and so on. Capable of self-teaching new algorithmic methods easily.Passionate about using data to drive strategy and business recommendation.Well-rounded top performer who is able to “crunch the numbers” one minute, and critically think through strategic issues the next.Excited to move fast and know how to prioritize and make critical decisions.A self-starter: you have started something on your own before -- an open-source project, a new project within a company or university, a start-up, or something else.Able to communicate as effectively when delivering complex data-driven findings to businesspeople, as when discussing machine-learning specifications with engineers.Senior candidates will often differentiate themselves with some of the following:Proven capability in applying machine learning methods to novel problems and driving quantifiable gains in outcome.Experience planning and executing work modules that span several months.Broad skillset that blurs the lines between data science and software engineering. Exceptional computational background (e.g., developed new algorithms and/or has a relevant PhD).Exceptional business background (e.g., managing client relationships on technical projects, experience at a top-tier consultancy and/or MBA from a leading program).Academic QualificationsCandidates should hold a very strong CS, math, science or similar degree from a leading program. PhD applicants are actively considered. Successful candidates will be comfortable in a fluid, entrepreneurial environment, but one that is focused on developing reusable software applications, not bespoke analytical solutions.Benefits and CultureActifai offers an extremely competitive compensation package, including equity, employer-covered health/vision/dental insurance (with an optional FSA), and 401k matching. Employees receive a generous PTO allowance, and can work both remotely and from our office in downtown Washington, D.C. Successful candidates will join a small team of ambitious, supportive co-workers with ample opportunities to take on responsibilities beyond their assigned role.For additional information on benefits & what it's like to work at Actifai, please visit actif.ai/careers.Finally, we highlight that excellence has no single mold, particularly in a field as rapidly evolving as AI. We're looking for excellent candidates of all backgrounds with strong business intuition and coding skills, and welcome applicants regardless of ethnic/national origin, gender, race, religious beliefs, disability, sexual orientation or age.A Note on the Interview ProcessActifai interviews share some common features with other technical hiring processes and have some important differences. These reflect the unique roles our employees play, which often involve early-stage development of products and environments where idea generation, product-market fit, and partner interaction may be significant aspects of their jobs.All our roles have technical interviews that test core engineering competencies, ability to discuss technical work, formalize generic problems into a quantitative system, problem-solve, and act as part of a team.We also ask case-study interview questions, which are less common for technical roles. Case studies are open-ended business problems that do not have set correct answers. They require the interviewee to consider the provided information, decide what is most important, and then build a structure to answer the key questions in discussion with the interviewer. We've incorporated these into our process because Actifai is, similarly, working on dynamic problems with many possible solutions. These challenges require business acumen, problem-solving skills, and the ability to think on your feet and prioritize information and actions.Our staff will often describe this unique mindset as not only wanting to write the code to solve a problem but also being able to define the problem that we are solving — and our interview process is designed to help employees showcase their skills in this area.
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Some key challenges will include: identifying external datasets and developing API or other methods for accessing them; fluidly self-educating on existing methods for modeling end-user behavior in a variety of contexts, or developing new methods for doing this when necessary; designing experiments to answer targeted questions; teaming with developers to embed algorithms in applications; understanding business economics, user motivation and other contextual information in order to guide analytical trade-offs, with a focus on “minimum viable algorithm” followed by intensive, iterative improvement; writing code that builds new companies and products.
Entry level candidates will likely have many of the following characteristics:Comfortable using scripting languages, and relational or NoSQL databases.Familiar with general-purpose machine learning methods, such as regression, decision trees, neural networks, Bayesian networks, and so on. Capable of self-teaching new algorithmic methods easily.Passionate about using data to drive strategy and business recommendation.Well-rounded top performer who is able to “crunch the numbers” one minute, and critically think through strategic issues the next.Excited to move fast and know how to prioritize and make critical decisions.A self-starter: you have started something on your own before -- an open-source project, a new project within a company or university, a start-up, or something else.Able to communicate as effectively when delivering complex data-driven findings to businesspeople, as when discussing machine-learning specifications with engineers.Senior candidates will often differentiate themselves with some of the following:Proven capability in applying machine learning methods to novel problems and driving quantifiable gains in outcome.Experience planning and executing work modules that span several months.Broad skillset that blurs the lines between data science and software engineering. Exceptional computational background (e.g., developed new algorithms and/or has a relevant PhD).Exceptional business background (e.g., managing client relationships on technical projects, experience at a top-tier consultancy and/or MBA from a leading program).Academic QualificationsCandidates should hold a very strong CS, math, science or similar degree from a leading program. PhD applicants are actively considered. Successful candidates will be comfortable in a fluid, entrepreneurial environment, but one that is focused on developing reusable software applications, not bespoke analytical solutions.Benefits and CultureActifai offers an extremely competitive compensation package, including equity, employer-covered health/vision/dental insurance (with an optional FSA), and 401k matching. Employees receive a generous PTO allowance, and can work both remotely and from our office in downtown Washington, D.C. Successful candidates will join a small team of ambitious, supportive co-workers with ample opportunities to take on responsibilities beyond their assigned role.For additional information on benefits & what it's like to work at Actifai, please visit actif.ai/careers.Finally, we highlight that excellence has no single mold, particularly in a field as rapidly evolving as AI. We're looking for excellent candidates of all backgrounds with strong business intuition and coding skills, and welcome applicants regardless of ethnic/national origin, gender, race, religious beliefs, disability, sexual orientation or age.A Note on the Interview ProcessActifai interviews share some common features with other technical hiring processes and have some important differences. These reflect the unique roles our employees play, which often involve early-stage development of products and environments where idea generation, product-market fit, and partner interaction may be significant aspects of their jobs.All our roles have technical interviews that test core engineering competencies, ability to discuss technical work, formalize generic problems into a quantitative system, problem-solve, and act as part of a team.We also ask case-study interview questions, which are less common for technical roles. Case studies are open-ended business problems that do not have set correct answers. They require the interviewee to consider the provided information, decide what is most important, and then build a structure to answer the key questions in discussion with the interviewer. We've incorporated these into our process because Actifai is, similarly, working on dynamic problems with many possible solutions. These challenges require business acumen, problem-solving skills, and the ability to think on your feet and prioritize information and actions.Our staff will often describe this unique mindset as not only wanting to write the code to solve a problem but also being able to define the problem that we are solving — and our interview process is designed to help employees showcase their skills in this area.
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