Data Scientist at MyShell

, Apac, Uganda -

Full Time

Start Date

Immediate

Expiry Date

26 Feb, 26

Salary

0.0

Posted On

28 Nov, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Architecture, Data Infrastructure, Experimentation Methodology, SQL, Python, Data Warehouse Modeling, A/B Testing, Statistical Testing, Data Analysis, Business Communication, Data Governance, Data Quality Monitoring, Growth Opportunities, Product Optimization, Data Culture, Experiment Design

Industry

Software Development

Description

About MyShell MyShell is revolutionizing the AI landscape by building an open ecosystem for AI-native apps. Our powerful platform and intuitive toolkit empower anyone to create, access, and benefit from AI-powered applications. Launched in April 2023, MyShell has quickly gained global traction, attracting a diverse community of creators and users. Our team of talented individuals from top institutions like MIT, Princeton, and Oxford is committed to fostering innovation in a supportive and transparent work environment. With funding from leading VCs, MyShell is poised to reshape the future of AI, making it accessible and integral to everyone's daily life. Join us on this thrilling journey as we redefine what's possible with AI. Overview Our company is in a phase of rapidly building out our data infrastructure and experimentation framework. Our current data table structures, field definitions, ID systems, and experiment pipelines carry significant legacy issues: inconsistent metric definitions, fragmented experiment processes between engineering and business teams, and high decision-making costs. We are looking for a Data Scientist with strong engineering skills, solid experimentation methodology, and deep business understanding to design and lead a unified data and experimentation framework across the company, enabling faster iteration and better decision‑making for all business lines. Responsibilities 1. Data Architecture & Infrastructure Review and refactor existing data table structures, field semantics, and key/ID systems to resolve legacy issues such as “one field with multiple meanings” Design and drive a unified data model and metric definitions; establish a company‑wide data dictionary and data standards Partner closely with engineering to participate in data warehouse modeling and data pipeline (ETL/ELT) design, improving data quality and maintainability 2. Experimentation System & Evaluation Framework Own the overall methodology and implementation path for A/B testing and other online experiments across the company Design experiment pipelines, including traffic allocation, tracking/instrumentation strategy, data collection, data storage, and analysis workflows Develop standardized experiment analysis frameworks and reusable templates, including core metrics, significance testing, sample size estimation, and evaluation guidelines 3. Business Partnership & Decision Support Deeply engage with core business lines and define problems and key metrics starting from product and business goals Based on the unified data system, provide structured data analysis and experiment recommendations to product and business teams Use data and experiment results to identify growth opportunities, product optimization directions, and potential risks, and clearly communicate findings to non‑technical stakeholders 4. Data Governance & Best Practices Promote data naming conventions, field definitions, and tracking standards, and ensure their adoption across the company Establish and maintain data quality monitoring mechanisms to detect and fix data issues Document and socialize internal best practices related to data and experimentation, helping to build a strong data culture and improve overall data usage efficiency Requirements 1. Education & Experience Bachelor’s degree or above in Computer Science, Statistics, Mathematics, Information Engineering, or related fields 3+ years of experience as a Data Scientist, Data Product Manager, Data Engineer, or Growth Analyst Experience building a data system from scratch or leading large‑scale data infrastructure re‑architecture is a strong plus 2. Technical Skills Strong SQL skills: capable of handling complex joins and large‑scale queries with attention to performance and maintainability Proficient in Python (or a similar language) for data cleaning, analysis/modeling, and developing automated analysis scripts Solid understanding of data warehouse modeling concepts (e.g., dimensional modeling, star/snowflake schemas) and data architecture Familiar with online experimentation (A/B testing), including metric design, experiment design, statistical testing, and sample size estimation 3. Business & Communication Skills Proven experience working closely with business teams and translating business problems into measurable, testable data and experiment questions Strong communication skills; able to collaborate effectively with product, business, and engineering stakeholders Highly self‑driven, with a strong sense of ownership for “making data and experimentation work well at the company” beyond just completing ad‑hoc analysis tasks Nice to Have End‑to‑end experience building an experimentation platform, metrics platform, or data governance framework at the company level Experience in Internet / SaaS / consumer products, with practical work on user behavior analysis, funnel analysis, and retention analysis Familiarity with common statistical modeling or machine learning methods, with hands‑on experience in use cases such as recommendation, pricing, ranking, or user segmentation We Hope You Are Someone Who Sees yourself not as a “report maintainer” but as the company‑level owner of data and experimentation systems Enjoys turning messy, fragmented data into something clear, unified, and reusable Wants your work to become foundational infrastructure that continuously supports company decisions and product iterations over the long term What We Offer Competitive salary and equity package, commensurate with experience and location. Flexible working hours and a fully remote work environment, with the ability to collaborate effectively across time zones. A dynamic and collaborative work environment that fosters innovation, growth, and professional development. The opportunity to work on cutting-edge technologies and help shape the future of AI, transforming industries and making a global impact.

Responsibilities

Design and lead a unified data and experimentation framework across the company. Engage with business lines to provide structured data analysis and experiment recommendations.