We are seeking a Senior Data Scientist with a strong background in analytics engineering to join our dynamic data science team. This role goes beyond data pipelining, modelling, and reporting, and involves using data to address partner and customer queries and concerns. Working in an agile and highly collaborative environment, we challenge traditional leadership paradigms. Our company values genuine transparency and deep respect, and as we continue to grow, we are looking for an experienced Data Scientist to join our team and oversee our crucial data infrastructure.

Objective

As a Senior Analytics Engineer/Data Scientist at Ajua, you will spearhead efforts to optimise the performance, integrity, and security of our data infrastructure and pipelines. Collaborating closely with our Engineering, Data, and Customer Success teams, you will ensure that customer needs are not only met but surpassed by providing actionable insights derived from data. We're seeking a candidate with extensive expertise in data infrastructure and pipelines, a deep understanding of machine learning algorithms, and strong skills in data visualization. In addition to having excellent problem-solving abilities, we value your capability to thrive in a collaborative team environment, driving innovation and excellence in every project.

What you will need

University degree (BA, BSc, etc.) in a quantitative discipline such as Statistics, Computer Science, Mathematics, Information Management, Economics or a related field.
Demonstrate a sense of ownership, a growth mindset, and the capability to propose scalable solutions.
Proven self-learning ability and quick adaptation to new knowledge and technical skills.
In-depth understanding of statistical analysis techniques and machine learning algorithms.
Strong command of analytics engineering tools such as SQL, dbt, Python, R, Prefect, Airflow, or similar programming languages.
Ability to craft complex queries and manipulate both SQL and NoSQL databases effectively.
Solid grasp of database management systems like MySQL, PostgreSQL, Oracle, or SQL Server.
Thorough understanding of data modelling concepts like dimensional modelling and database technologies.
Familiarity with various warehouse technologies such as Snowflake, BigQuery, and Redshift.
Comfort and proficiency in utilising different cloud platforms (AWS, GCP, Azure) and employing various computing and analytics tools (S3, Athena, Glue, Quicksight, GCS, Dataproc).
Capability to thrive both independently and collaboratively in a fast-paced environment.
Excellent communication and interpersonal skills.

Responsibilities

We are seeking a Senior Data Scientist with a strong background in analytics engineering to join our dynamic data science team. This role goes beyond data pipelining, modelling, and reporting, and involves using data to address partner and customer queries and concerns. Working in an agile and highly collaborative environment, we challenge traditional leadership paradigms. Our company values genuine transparency and deep respect, and as we continue to grow, we are looking for an experienced Data Scientist to join our team and oversee our crucial data infrastructure.

Objective

As a Senior Analytics Engineer/Data Scientist at Ajua, you will spearhead efforts to optimise the performance, integrity, and security of our data infrastructure and pipelines. Collaborating closely with our Engineering, Data, and Customer Success teams, you will ensure that customer needs are not only met but surpassed by providing actionable insights derived from data. We're seeking a candidate with extensive expertise in data infrastructure and pipelines, a deep understanding of machine learning algorithms, and strong skills in data visualization. In addition to having excellent problem-solving abilities, we value your capability to thrive in a collaborative team environment, driving innovation and excellence in every project.

What you will need

University degree (BA, BSc, etc.) in a quantitative discipline such as Statistics, Computer Science, Mathematics, Information Management, Economics or a related field.
Demonstrate a sense of ownership, a growth mindset, and the capability to propose scalable solutions.
Proven self-learning ability and quick adaptation to new knowledge and technical skills.
In-depth understanding of statistical analysis techniques and machine learning algorithms.
Strong command of analytics engineering tools such as SQL, dbt, Python, R, Prefect, Airflow, or similar programming languages.
Ability to craft complex queries and manipulate both SQL and NoSQL databases effectively.
Solid grasp of database management systems like MySQL, PostgreSQL, Oracle, or SQL Server.
Thorough understanding of data modelling concepts like dimensional modelling and database technologies.
Familiarity with various warehouse technologies such as Snowflake, BigQuery, and Redshift.
Comfort and proficiency in utilising different cloud platforms (AWS, GCP, Azure) and employing various computing and analytics tools (S3, Athena, Glue, Quicksight, GCS, Dataproc).
Capability to thrive both independently and collaboratively in a fast-paced environment.
Excellent communication and interpersonal skills.

Building, developing, and maintaining automated dashboards to monitor business and technical metrics.
Analyzing complex data of technical platforms to drive insightful findings and translating them into meaningful, actionable recommendations for our clientele
Collaborate with internal data teams, customer success teams and customer engineer teams to consolidate requirements, understand needs, and deliver necessary tools.
Designing, building, monitoring and maintaining data pipelines/workflows to meet downstream customer needs.
Designing, and building supporting products of data quality to ensure data sources are reliable and relevant.
Maintain and improve or remodel existing data science models.
Tracking a daily log of data quality issues found within customer experience data
Contributing to the Data & Analytics Innovation team to prototype new models, conduct exploratory data analysis, and research data science
Contributing to the formulation of modelling solutions across different industries
Getting exposure to the integration of diverse big data sources
Researching new modelling techniques as appropriate for a specific solution
Creating detailed documentation outlining the design and technical specifications of each solution
Assist with pitches by providing social listening, competitive analysis and secondary research to inform strategy and creative development
Ad-hoc Reporting & Data Analysis duties or other responsibilities as required.

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