<p><p><b>Description : </b><br/><br/>We're looking for a highly skilled Senior Data Scientist & Analytics Lead to join our team.
In this pivotal role, you'll be a force multiplier, leveraging data to drive strategic decisions, build scalable analytics solutions, and develop AI-powered systems.
You'll partner with engineering, product, and leadership to own the full analytics lifecycle from building robust data pipelines to deploying advanced models and delivering clear, actionable insights.<br/><br/>This is a unique opportunity for a hands-on technical leader who is passionate about both deep-dive analysis and building the foundational data infrastructure that powers our growth.
You'll be a key voice in shaping our data strategy, and as we grow, this role is perfect for someone looking to build and lead a data team.<br/><br/><b>Responsibilities : </b><br/><br/><b>Analytics and Strategic Insights :</b></p><p><p><b><br/></b></p>- Transform complex, messy data into clear, actionable insights and narratives that directly impact product, marketing, and business strategy.<br/><br/></p><p>- Conduct in-depth exploratory analysis to identify growth opportunities, surface unusual patterns, and provide data-driven recommendations.<br/><br/></p><p>- Build intuitive, client-facing dashboards and reports that empower both internal teams and customers to make strategic decisions.<br/><br/><b>Data Engineering and Architecture : </b><br/><br/></p><p>- Design, build, and maintain end-to-end ETL processes and data pipelines to ensure data integrity, security, and compliance.<br/><br/></p><p>- Own our data warehouse, including ingestion, transformation, and orchestration, ensuring it is scalable and performant.<br/><br/></p><p>- Design and optimise data models to ensure they are well-documented and support analysis, reporting, and AI use cases.<br/><br/></p><p>- Collaborate with engineering teams to improve event logging and ensure data quality across all systems.<br/><br/><b>AI and Predictive Modelling : </b><br/><br/></p><p>- Develop, train, and deploy predictive models for various use cases, including anomaly detection, risk assessment, and trend forecasting.<br/><br/></p><p>- Deep expertise in ML algorithms (including supervised and unsupervised methods), loss functions, regularisation techniques, and probability distributions<br/><br/></p><p>- Utilise AI and LLMs to parse unstructured data and automate complex tasks, continually refining workflows and prompts.<br/><br/></p><p>- Monitor model performance and agent-generated data signals to detect anomalies and key drivers.<br/><br/><b>Requirements : </b><br/><br/></p><p>- Experience : 4+ years of hands-on experience in data science, analytics, or data engineering, ideally in a fast-paced, startup environment.<br/><br/></p><p>- SQL & Data Modelling Expertise : You are an expert in SQL and have a strong understanding of data modelling, schema design, and modern data warehouses (e.
g., Databricks, BigQuery, Snowflake, Redshift).</p><p><br/></p><p>- Python Proficiency : You are fluent in Python and have practical experience with machine </p><p>learning frameworks (e.
g., TensorFlow, PyTorch, Scikit-learn).<br/><br/></p><p>- Firm grasp of statistical and stochastic models, and hypothesis testing(e.
g., t-tests, ANOVA, </p><p>chi-square for inferential stats and p-value analysis).
Proficiency in optimisation algorithms like </p><p>Bayesian optimisation, genetic algorithms, and particle swarm optimisation.<br/><br/></p><p>- Data Stack Experience : You have hands-on experience with modern data stacks and tools for </p><p>ingestion, transformation, and orchestration.<br/><br/></p><p>- Communication & Business Acumen : You can translate technical findings into strategic recommendations and communicate effectively with both technical and non-technical stakeholders.<br/><br/></p><p>- Experience with BI tools like Metabase, Looker, or Tableau.<br/><br/></p><p>- Familiarity with AI/LLMs (prompting, evaluation, and fine-tuning).<br/><br/></p><p>- Experience with analytics platforms such as GA4 Adjust, Mixpanel, Amplitude, Firebase, </p><p>AppsFlyer, and HotJar.<br/><br/></p><p>- Experience with advertising engines like Google Ads, Meta Ads, or TikTok Ads, including data </p><p>extraction, analysis, and optimisation.</p><br/></p> (ref:hirist.tech)