Data Science Manager - Nift

Nift is disrupting performance marketing, delivering millions of new customers to brands every month, and we are actively looking for a Data Science Manager to join our team. We are a well-managed, data-driven, cash-flow-positive company with a customer-first mindset. After four years of consecutive 100% YoY growth, we aren't slowing down – we're ready to scale to be one of the largest sources of customer acquisition in the U.S and soon globally. Our investors are the same tech insiders who invested in Fitbit, Warby Parker, Wayfair, and Twitter, and we are ready to demonstrate impact at the same scale as those companies.

The role:

As a hands-on manager, you will lead our entire Data Science team and report to the CEO. You will mentor, direct, and manage a staff of five, composed of Data Scientists, MLEs, and Data Analysts. The Data Science team plays a crucial role in the success of Nift by developing and deploying real time consumer oriented models that are at the core of our business, consumer satisfaction and revenue, analyzing large datasets, identifying patterns, and making recommendations to impact business outcomes. You will collaborate closely with cross-functional teams to translate insights into actionable solutions. To lead this team, you will need expertise in analyzing data and statistics, machine learning, modeling, and data mining techniques.

What you will do:

• Lead, build, inspire, mentor and grow a world class high performance team to structure ambiguous business challenges into actionable plans. Ensure that your team is producing consistently trustworthy and high-quality technical outputs that positively influence the business
• Provide technical guidance and mentorship to team members. Weigh the pros and cons of various solutions and propose the best path. Set clear goals and expectations for the team and provide regular feedback and support to help team members achieve objectives
• Using strong business acumen, you and your team will explore / analyze large data sets to gain insights and identify patterns / trends relevant to your modeling objectives, and apply root cause analysis to drive growth and achieve tangible business outcomes 
• Translate and refine business questions into tractable analysis, evaluation metrics, or mathematical models
• Collaborate with cross-functional teams to help identify and answer important "why" questions, understand business requirements and translate them into data-driven solutions
• Communicate complex analytical findings, insights, updates, and risks to both technical and non-technical stakeholders proactively in a clear and concise manner
• You and your team will be responsible for designing, building, evaluating new/existing consumer and brand experiences across the platform. Each of these brings its own complexity and challenges, providing exposure to a wide variety of data science problems, including selecting appropriate algorithms, feature engineering, model training, and evaluation
• You and your team will assess, improve, and optimize the performance and accuracy of models using appropriate evaluation metrics, identify areas of improvement, refine models based on new data and evolving business needs, reduce bias or overfitting, and enhance the efficiency of the algorithms. This includes conducting experiments, cross-validation, and providing actionable recommendations
• Stay up-to-date with the latest advancements in data science, machine learning, and recommendation system technologies, and apply them to solve business challenges
• Own the process of gathering, sourcing, extracting, and compiling data across sources via relevant tools (e.g., SQL, R, Python)
• Champion QA, adopting standards, methods, metrics, and processes. Independently format, re-structure, and/or validate data to ensure quality, and review the dataset to ensure it is ready for analysis. This involves data cleaning, preprocessing, and transforming data into a suitable format for analysis & modeling
• Be responsible for the machine learning operations in production

What You Need:

• Master's or Ph.D. in a quantitative field such as Computer Science, Statistics, Applied Mathematics, Economics, Physics, or a related discipline
• At least 6 years of experience leading a team of ML engineers, Data Scientists, and Analysts including hiring, mentoring, and performance management
• Previous hands-on experience as either a data scientist, algorithmic engineer, or machine learning engineer in a technology company
• Experience with real time model scoring in production with millions of consumers, first and third party data, and production ML/AI technologies. 
• Proficiency in programming languages such as Python or R, along with experience in data manipulation and analysis using libraries like NumPy, Pandas, or SciPy
• Experience in ML-Ops and data pipelines, ML frameworks/libraries such as AWS Sagemaker, scikit-learn or equivalent
• Strong understanding of ML algorithms, statistical techniques, and data analysis methodologies
• Experience with data processing, feature engineering and model evaluation techniques, building ML applications/services with cloud scalability
• Proficiency in SQL & Postgres
• Comfortable leading a team that is building and deploying into production, predictive models and recommendation / ranking systems using statistical modeling, machine learning, and data mining techniques
• An understanding of various machine learning techniques, such as regression, classification, clustering, dimensionality reduction, and ensemble methods
• Familiarity with popular algorithms like decision trees, random forests, boosted trees, and regularized regression
• Problem-solving skills and the ability to think critically to develop innovative solutions
• Excellent people, communication and collaboration skills to effectively work with cross-functional teams and present complex findings
• Very organized with an attention to details, strong prioritization skills, proven success delivering multiple projects on time 

What You Get:

• Competitive compensation and benefits (401K, Med/Dental/Vision)
• Great opportunity to join a growing, cash-flow-positive company
• Measurable personal impact on Nift's revenue, company growth, scale, and future success
• Work remotely